{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\dpeksen\Dropbox\Detraz & Peksen paper\Data Files\RandRData and Do Files\DetrazPeksenReplicationLog.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}30 Apr 2015, 15:00:19

{com}. do "C:\Users\dpeksen\AppData\Local\Temp\STD00000000.tmp"
{txt}
{com}. *Replication Do File: Detraz, Nicole and Dursun Peksen. "The Effect of IMF Programs on Women's Economic and Political Rights" (International Interactions)
. 
. *Table I WECON Rights
. cmp setup
{txt}
{com}. cmp(wecon = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme  lagweconglobe trend lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res} -850.8261
{txt}Iteration 2:   log likelihood = {res}-826.22945
{txt}Iteration 3:   log likelihood = {res}-825.49629
{txt}Iteration 4:   log likelihood = {res}-825.49434

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}14{txt}){col 67}= {res}    910.13
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-825.49434{txt}{col 51}Pseudo R2{col 67}= {res}    0.3554

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0792021{col 27}{space 2} .0754541{col 38}{space 1}   -1.05{col 47}{space 3}0.294{col 55}{space 4}-.2270894{col 68}{space 3} .0686853
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0213197{col 27}{space 2} .0064325{col 38}{space 1}    3.31{col 47}{space 3}0.001{col 55}{space 4} .0087123{col 68}{space 3} .0339271
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0075054{col 27}{space 2} .0062918{col 38}{space 1}    1.19{col 47}{space 3}0.233{col 55}{space 4}-.0048263{col 68}{space 3} .0198371
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2}  .086061{col 27}{space 2} .0414464{col 38}{space 1}    2.08{col 47}{space 3}0.038{col 55}{space 4} .0048275{col 68}{space 3} .1672945
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.4053029{col 27}{space 2} .2095197{col 38}{space 1}   -1.93{col 47}{space 3}0.053{col 55}{space 4} -.815954{col 68}{space 3} .0053481
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2910368{col 27}{space 2} .0981001{col 38}{space 1}    2.97{col 47}{space 3}0.003{col 55}{space 4} .0987642{col 68}{space 3} .4833094
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0852425{col 27}{space 2} .0256578{col 38}{space 1}   -3.32{col 47}{space 3}0.001{col 55}{space 4}-.1355308{col 68}{space 3}-.0349542
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2140617{col 27}{space 2} .0934324{col 38}{space 1}   -2.29{col 47}{space 3}0.022{col 55}{space 4}-.3971859{col 68}{space 3}-.0309375
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} .0591452{col 27}{space 2} .1209291{col 38}{space 1}    0.49{col 47}{space 3}0.625{col 55}{space 4}-.1778716{col 68}{space 3} .2961619
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.088336{col 27}{space 2}  .512255{col 38}{space 1}   -4.08{col 47}{space 3}0.000{col 55}{space 4}-3.092337{col 68}{space 3}-1.084334
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0187667{col 27}{space 2} .0075491{col 38}{space 1}   -2.49{col 47}{space 3}0.013{col 55}{space 4}-.0335627{col 68}{space 3}-.0039707
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.448391{col 27}{space 2} .1356105{col 38}{space 1}   10.68{col 47}{space 3}0.000{col 55}{space 4}   1.1826{col 68}{space 3} 1.714183
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.331201{col 27}{space 2}  .160347{col 38}{space 1}   20.77{col 47}{space 3}0.000{col 55}{space 4} 3.016926{col 68}{space 3} 3.645475
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.814471{col 27}{space 2} .4332275{col 38}{space 1}   11.11{col 47}{space 3}0.000{col 55}{space 4} 3.965361{col 68}{space 3} 5.663582
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2}-40.73551{col 27}{space 2} 14.76944{col 55}{space 4}-69.68308{col 68}{space 3}-11.78794
{txt}        /cut2 {c |}{col 15}{res}{space 2}-37.46631{col 27}{space 2} 14.75814{col 55}{space 4}-66.39173{col 68}{space 3}-8.540893
{txt}        /cut3 {c |}{col 15}{res}{space 2}-34.75367{col 27}{space 2} 14.75698{col 55}{space 4}-63.67681{col 68}{space 3}-5.830522
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 5010.538.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}14{txt}){col 67}= {res}    710.52
{txt}Log pseudolikelihood = {res} -2104.884{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.7807704{col 27}{space 2}  .211669{col 38}{space 1}   -3.69{col 47}{space 3}0.000{col 55}{space 4}-1.195634{col 68}{space 3}-.3659068
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0228105{col 27}{space 2} .0078681{col 38}{space 1}    2.90{col 47}{space 3}0.004{col 55}{space 4} .0073894{col 68}{space 3} .0382317
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} -.000595{col 27}{space 2} .0063795{col 38}{space 1}   -0.09{col 47}{space 3}0.926{col 55}{space 4}-.0130985{col 68}{space 3} .0119086
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0409057{col 27}{space 2} .0423464{col 38}{space 1}    0.97{col 47}{space 3}0.334{col 55}{space 4}-.0420918{col 68}{space 3} .1239031
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.3540519{col 27}{space 2} .1829169{col 38}{space 1}   -1.94{col 47}{space 3}0.053{col 55}{space 4}-.7125625{col 68}{space 3} .0044586
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2441972{col 27}{space 2} .1050495{col 38}{space 1}    2.32{col 47}{space 3}0.020{col 55}{space 4}  .038304{col 68}{space 3} .4500904
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0882692{col 27}{space 2} .0272657{col 38}{space 1}   -3.24{col 47}{space 3}0.001{col 55}{space 4} -.141709{col 68}{space 3}-.0348294
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2891764{col 27}{space 2} .1040847{col 38}{space 1}   -2.78{col 47}{space 3}0.005{col 55}{space 4}-.4931786{col 68}{space 3}-.0851742
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.0404367{col 27}{space 2} .2132469{col 38}{space 1}   -0.19{col 47}{space 3}0.850{col 55}{space 4} -.458393{col 68}{space 3} .3775196
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.084616{col 27}{space 2}   .55005{col 38}{space 1}   -3.79{col 47}{space 3}0.000{col 55}{space 4}-3.162694{col 68}{space 3}-1.006538
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0096455{col 27}{space 2} .0010567{col 38}{space 1}   -9.13{col 47}{space 3}0.000{col 55}{space 4}-.0117166{col 68}{space 3}-.0075744
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.353499{col 27}{space 2} .2750703{col 38}{space 1}    4.92{col 47}{space 3}0.000{col 55}{space 4} .8143709{col 68}{space 3} 1.892627
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.103063{col 27}{space 2} .3409299{col 38}{space 1}    9.10{col 47}{space 3}0.000{col 55}{space 4} 2.434853{col 68}{space 3} 3.771273
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.475897{col 27}{space 2} .5157087{col 38}{space 1}    8.68{col 47}{space 3}0.000{col 55}{space 4} 3.465126{col 68}{space 3} 5.486667
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1969535{col 27}{space 2} .0336296{col 38}{space 1}   -5.86{col 47}{space 3}0.000{col 55}{space 4}-.2628663{col 68}{space 3}-.1310407
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2}  .002313{col 27}{space 2} .0075986{col 38}{space 1}    0.30{col 47}{space 3}0.761{col 55}{space 4}-.0125799{col 68}{space 3} .0172059
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2547122{col 27}{space 2} .1146442{col 38}{space 1}   -2.22{col 47}{space 3}0.026{col 55}{space 4}-.4794106{col 68}{space 3}-.0300138
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000173{col 27}{space 2} .0000186{col 38}{space 1}    0.93{col 47}{space 3}0.352{col 55}{space 4}-.0000192{col 68}{space 3} .0000538
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0515009{col 27}{space 2} .1076944{col 38}{space 1}   -0.48{col 47}{space 3}0.632{col 55}{space 4}-.2625781{col 68}{space 3} .1595763
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0188463{col 27}{space 2} .0225083{col 38}{space 1}   -0.84{col 47}{space 3}0.402{col 55}{space 4}-.0629618{col 68}{space 3} .0252691
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .2407519{col 27}{space 2} .1244306{col 38}{space 1}    1.93{col 47}{space 3}0.053{col 55}{space 4}-.0031275{col 68}{space 3} .4846314
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8719947{col 27}{space 2} .2602257{col 38}{space 1}    3.35{col 47}{space 3}0.001{col 55}{space 4} .3619618{col 68}{space 3} 1.382028
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0869125{col 27}{space 2}  .183514{col 38}{space 1}    0.47{col 47}{space 3}0.636{col 55}{space 4}-.2727683{col 68}{space 3} .4465933
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4601734{col 27}{space 2} .2070636{col 38}{space 1}    2.22{col 47}{space 3}0.026{col 55}{space 4} .0543362{col 68}{space 3} .8660105
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9505074{col 27}{space 2} .2939043{col 38}{space 1}    3.23{col 47}{space 3}0.001{col 55}{space 4} .3744655{col 68}{space 3} 1.526549
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.1837824{col 27}{space 2}  .336743{col 38}{space 1}   -0.55{col 47}{space 3}0.585{col 55}{space 4}-.8437866{col 68}{space 3} .4762217
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6348849{col 27}{space 2}  .222543{col 38}{space 1}    2.85{col 47}{space 3}0.004{col 55}{space 4} .1987086{col 68}{space 3} 1.071061
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1518518{col 27}{space 2} .2518944{col 38}{space 1}    0.60{col 47}{space 3}0.547{col 55}{space 4} -.341852{col 68}{space 3} .6455557
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.030071{col 27}{space 2}  1.01139{col 38}{space 1}    1.02{col 47}{space 3}0.308{col 55}{space 4}-.9522163{col 68}{space 3} 3.012358
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .5123104{col 27}{space 2} .1500733{col 38}{space 1}    3.41{col 47}{space 3}0.001{col 55}{space 4} .2181721{col 68}{space 3} .8064487
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2}-23.17269{col 27}{space 2} 1.874536{col 38}{space 1}  -12.36{col 47}{space 3}0.000{col 55}{space 4}-26.84671{col 68}{space 3}-19.49867
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2}-20.08235{col 27}{space 2} 1.875668{col 38}{space 1}  -10.71{col 47}{space 3}0.000{col 55}{space 4}-23.75859{col 68}{space 3}-16.40611
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2}-17.51061{col 27}{space 2} 1.961529{col 38}{space 1}   -8.93{col 47}{space 3}0.000{col 55}{space 4}-21.35514{col 68}{space 3}-13.66609
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .4717434{col 27}{space 2} .1166757{col 55}{space 4} .2147751{col 68}{space 3} .6676265
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wecon = imfdummy imfpolity polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme  lagweconglobe trend lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res}-850.31153
{txt}Iteration 2:   log likelihood = {res} -825.5572
{txt}Iteration 3:   log likelihood = {res}-824.81045
{txt}Iteration 4:   log likelihood = {res}-824.80846

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}    911.50
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-824.80846{txt}{col 51}Pseudo R2{col 67}= {res}    0.3559

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.2486587{col 27}{space 2} .1633181{col 38}{space 1}   -1.52{col 47}{space 3}0.128{col 55}{space 4}-.5687563{col 68}{space 3} .0714389
{txt}{space 4}imfpolity {c |}{col 15}{res}{space 2} .0132994{col 27}{space 2} .0113611{col 38}{space 1}    1.17{col 47}{space 3}0.242{col 55}{space 4}-.0089679{col 68}{space 3} .0355667
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0163247{col 27}{space 2} .0077177{col 38}{space 1}    2.12{col 47}{space 3}0.034{col 55}{space 4} .0011983{col 68}{space 3} .0314511
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0070597{col 27}{space 2}  .006306{col 38}{space 1}    1.12{col 47}{space 3}0.263{col 55}{space 4}-.0052999{col 68}{space 3} .0194192
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0869123{col 27}{space 2} .0414672{col 38}{space 1}    2.10{col 47}{space 3}0.036{col 55}{space 4} .0056382{col 68}{space 3} .1681864
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2} -.411965{col 27}{space 2} .2096681{col 38}{space 1}   -1.96{col 47}{space 3}0.049{col 55}{space 4}-.8229068{col 68}{space 3}-.0010231
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2919203{col 27}{space 2} .0981619{col 38}{space 1}    2.97{col 47}{space 3}0.003{col 55}{space 4} .0995265{col 68}{space 3} .4843141
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0856388{col 27}{space 2} .0256937{col 38}{space 1}   -3.33{col 47}{space 3}0.001{col 55}{space 4}-.1359975{col 68}{space 3}  -.03528
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2052681{col 27}{space 2} .0938172{col 38}{space 1}   -2.19{col 47}{space 3}0.029{col 55}{space 4}-.3891464{col 68}{space 3}-.0213898
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} .0338121{col 27}{space 2} .1229079{col 38}{space 1}    0.28{col 47}{space 3}0.783{col 55}{space 4}-.2070829{col 68}{space 3} .2747071
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.073086{col 27}{space 2} .5125702{col 38}{space 1}   -4.04{col 47}{space 3}0.000{col 55}{space 4}-3.077705{col 68}{space 3}-1.068467
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0190919{col 27}{space 2} .0075569{col 38}{space 1}   -2.53{col 47}{space 3}0.012{col 55}{space 4}-.0339032{col 68}{space 3}-.0042806
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.450402{col 27}{space 2} .1357349{col 38}{space 1}   10.69{col 47}{space 3}0.000{col 55}{space 4} 1.184366{col 68}{space 3} 1.716437
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.340768{col 27}{space 2} .1606698{col 38}{space 1}   20.79{col 47}{space 3}0.000{col 55}{space 4} 3.025861{col 68}{space 3} 3.655675
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.836551{col 27}{space 2} .4338458{col 38}{space 1}   11.15{col 47}{space 3}0.000{col 55}{space 4} 3.986229{col 68}{space 3} 5.686873
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2}-41.43308{col 27}{space 2} 14.78697{col 55}{space 4}  -70.415{col 68}{space 3}-12.45115
{txt}        /cut2 {c |}{col 15}{res}{space 2}-38.15862{col 27}{space 2} 14.77549{col 55}{space 4}-67.11805{col 68}{space 3}-9.199192
{txt}        /cut3 {c |}{col 15}{res}{space 2}-35.44771{col 27}{space 2}  14.7742{col 55}{space 4} -64.4046{col 68}{space 3}-6.490819
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 5278.6519.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}    740.01
{txt}Log pseudolikelihood = {res}-2104.0951{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.9569721{col 27}{space 2} .2668142{col 38}{space 1}   -3.59{col 47}{space 3}0.000{col 55}{space 4}-1.479918{col 68}{space 3}-.4340259
{txt}{space 4}imfpolity {c |}{col 15}{res}{space 2} .0134011{col 27}{space 2} .0096714{col 38}{space 1}    1.39{col 47}{space 3}0.166{col 55}{space 4}-.0055546{col 68}{space 3} .0323567
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0177539{col 27}{space 2} .0086985{col 38}{space 1}    2.04{col 47}{space 3}0.041{col 55}{space 4} .0007051{col 68}{space 3} .0348027
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0011175{col 27}{space 2} .0065174{col 38}{space 1}   -0.17{col 47}{space 3}0.864{col 55}{space 4}-.0138915{col 68}{space 3} .0116564
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0415673{col 27}{space 2}  .042012{col 38}{space 1}    0.99{col 47}{space 3}0.322{col 55}{space 4}-.0407748{col 68}{space 3} .1239094
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.3593924{col 27}{space 2} .1832355{col 38}{space 1}   -1.96{col 47}{space 3}0.050{col 55}{space 4}-.7185274{col 68}{space 3}-.0002574
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2}   .24524{col 27}{space 2}  .105302{col 38}{space 1}    2.33{col 47}{space 3}0.020{col 55}{space 4} .0388518{col 68}{space 3} .4516282
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0886385{col 27}{space 2} .0272197{col 38}{space 1}   -3.26{col 47}{space 3}0.001{col 55}{space 4}-.1419881{col 68}{space 3}-.0352888
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2809025{col 27}{space 2} .1049569{col 38}{space 1}   -2.68{col 47}{space 3}0.007{col 55}{space 4}-.4866143{col 68}{space 3}-.0751908
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.0669626{col 27}{space 2} .2142401{col 38}{space 1}   -0.31{col 47}{space 3}0.755{col 55}{space 4}-.4868656{col 68}{space 3} .3529404
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.067488{col 27}{space 2} .5476234{col 38}{space 1}   -3.78{col 47}{space 3}0.000{col 55}{space 4} -3.14081{col 68}{space 3} -.994166
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0099479{col 27}{space 2} .0010588{col 38}{space 1}   -9.40{col 47}{space 3}0.000{col 55}{space 4}-.0120232{col 68}{space 3}-.0078726
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.353802{col 27}{space 2} .2755907{col 38}{space 1}    4.91{col 47}{space 3}0.000{col 55}{space 4} .8136544{col 68}{space 3}  1.89395
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.108742{col 27}{space 2} .3422216{col 38}{space 1}    9.08{col 47}{space 3}0.000{col 55}{space 4}    2.438{col 68}{space 3} 3.779484
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.490674{col 27}{space 2} .5182091{col 38}{space 1}    8.67{col 47}{space 3}0.000{col 55}{space 4} 3.475003{col 68}{space 3} 5.506345
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1974643{col 27}{space 2}  .033697{col 38}{space 1}   -5.86{col 47}{space 3}0.000{col 55}{space 4}-.2635091{col 68}{space 3}-.1314194
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0023423{col 27}{space 2} .0076015{col 38}{space 1}    0.31{col 47}{space 3}0.758{col 55}{space 4}-.0125564{col 68}{space 3} .0172411
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2552774{col 27}{space 2} .1146501{col 38}{space 1}   -2.23{col 47}{space 3}0.026{col 55}{space 4}-.4799875{col 68}{space 3}-.0305672
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000171{col 27}{space 2} .0000186{col 38}{space 1}    0.92{col 47}{space 3}0.357{col 55}{space 4}-.0000193{col 68}{space 3} .0000536
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0515332{col 27}{space 2} .1076203{col 38}{space 1}   -0.48{col 47}{space 3}0.632{col 55}{space 4}-.2624651{col 68}{space 3} .1593988
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} -.018849{col 27}{space 2} .0225178{col 38}{space 1}   -0.84{col 47}{space 3}0.403{col 55}{space 4}-.0629831{col 68}{space 3} .0252851
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .2417382{col 27}{space 2} .1244388{col 38}{space 1}    1.94{col 47}{space 3}0.052{col 55}{space 4}-.0021572{col 68}{space 3} .4856337
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8699857{col 27}{space 2} .2602566{col 38}{space 1}    3.34{col 47}{space 3}0.001{col 55}{space 4} .3598921{col 68}{space 3} 1.380079
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0844698{col 27}{space 2} .1830387{col 38}{space 1}    0.46{col 47}{space 3}0.644{col 55}{space 4}-.2742794{col 68}{space 3}  .443219
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4579943{col 27}{space 2} .2074615{col 38}{space 1}    2.21{col 47}{space 3}0.027{col 55}{space 4} .0513772{col 68}{space 3} .8646113
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2}  .951507{col 27}{space 2} .2942256{col 38}{space 1}    3.23{col 47}{space 3}0.001{col 55}{space 4} .3748355{col 68}{space 3} 1.528179
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.1793948{col 27}{space 2} .3370806{col 38}{space 1}   -0.53{col 47}{space 3}0.595{col 55}{space 4}-.8400606{col 68}{space 3}  .481271
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6349645{col 27}{space 2} .2229513{col 38}{space 1}    2.85{col 47}{space 3}0.004{col 55}{space 4}  .197988{col 68}{space 3} 1.071941
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1547909{col 27}{space 2} .2526253{col 38}{space 1}    0.61{col 47}{space 3}0.540{col 55}{space 4}-.3403455{col 68}{space 3} .6499273
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.033478{col 27}{space 2} 1.012041{col 38}{space 1}    1.02{col 47}{space 3}0.307{col 55}{space 4}-.9500854{col 68}{space 3} 3.017042
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .5171088{col 27}{space 2} .1518656{col 38}{space 1}    3.41{col 47}{space 3}0.001{col 55}{space 4} .2194577{col 68}{space 3} .8147599
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2}-23.82653{col 27}{space 2} 1.883271{col 38}{space 1}  -12.65{col 47}{space 3}0.000{col 55}{space 4}-27.51767{col 68}{space 3}-20.13539
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2}-20.73368{col 27}{space 2} 1.884131{col 38}{space 1}  -11.00{col 47}{space 3}0.000{col 55}{space 4}-24.42651{col 68}{space 3}-17.04085
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2}-18.16686{col 27}{space 2} 1.968167{col 38}{space 1}   -9.23{col 47}{space 3}0.000{col 55}{space 4}-22.02439{col 68}{space 3}-14.30932
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .4754655{col 27}{space 2} .1175337{col 55}{space 4} .2160011{col 68}{space 3} .6722077
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wecon = imfdummy imfgdp polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme  lagweconglobe trend lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res} -849.3791
{txt}Iteration 2:   log likelihood = {res}-824.25578
{txt}Iteration 3:   log likelihood = {res}-823.47707
{txt}Iteration 4:   log likelihood = {res}-823.47488

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}    914.17
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-823.47488{txt}{col 51}Pseudo R2{col 67}= {res}    0.3569

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.1924656{col 27}{space 2} .0943169{col 38}{space 1}   -2.04{col 47}{space 3}0.041{col 55}{space 4}-.3773233{col 68}{space 3}-.0076078
{txt}{space 7}imfgdp {c |}{col 15}{res}{space 2} .0581045{col 27}{space 2} .0287592{col 38}{space 1}    2.02{col 47}{space 3}0.043{col 55}{space 4} .0017375{col 68}{space 3} .1144715
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0188941{col 27}{space 2} .0065488{col 38}{space 1}    2.89{col 47}{space 3}0.004{col 55}{space 4} .0060587{col 68}{space 3} .0317295
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0055147{col 27}{space 2} .0063829{col 38}{space 1}    0.86{col 47}{space 3}0.388{col 55}{space 4}-.0069956{col 68}{space 3}  .018025
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2}  .081477{col 27}{space 2} .0415688{col 38}{space 1}    1.96{col 47}{space 3}0.050{col 55}{space 4} 3.52e-06{col 68}{space 3} .1629504
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.3879422{col 27}{space 2}  .210018{col 38}{space 1}   -1.85{col 47}{space 3}0.065{col 55}{space 4}-.7995699{col 68}{space 3} .0236855
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2703048{col 27}{space 2}  .098708{col 38}{space 1}    2.74{col 47}{space 3}0.006{col 55}{space 4} .0768407{col 68}{space 3} .4637689
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0884892{col 27}{space 2} .0257381{col 38}{space 1}   -3.44{col 47}{space 3}0.001{col 55}{space 4} -.138935{col 68}{space 3}-.0380434
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2046987{col 27}{space 2} .0937407{col 38}{space 1}   -2.18{col 47}{space 3}0.029{col 55}{space 4}-.3884272{col 68}{space 3}-.0209703
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}  .033236{col 27}{space 2} .1217533{col 38}{space 1}    0.27{col 47}{space 3}0.785{col 55}{space 4}-.2053961{col 68}{space 3}  .271868
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.105492{col 27}{space 2} .5130865{col 38}{space 1}   -4.10{col 47}{space 3}0.000{col 55}{space 4}-3.111123{col 68}{space 3}-1.099861
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0171009{col 27}{space 2} .0075998{col 38}{space 1}   -2.25{col 47}{space 3}0.024{col 55}{space 4}-.0319962{col 68}{space 3}-.0022055
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.455012{col 27}{space 2} .1359278{col 38}{space 1}   10.70{col 47}{space 3}0.000{col 55}{space 4} 1.188598{col 68}{space 3} 1.721425
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2}  3.33351{col 27}{space 2} .1606711{col 38}{space 1}   20.75{col 47}{space 3}0.000{col 55}{space 4}   3.0186{col 68}{space 3} 3.648419
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.813521{col 27}{space 2} .4329452{col 38}{space 1}   11.12{col 47}{space 3}0.000{col 55}{space 4} 3.964964{col 68}{space 3} 5.662078
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2}-37.57173{col 27}{space 2} 14.86258{col 55}{space 4}-66.70185{col 68}{space 3}-8.441619
{txt}        /cut2 {c |}{col 15}{res}{space 2}-34.29227{col 27}{space 2} 14.85196{col 55}{space 4}-63.40158{col 68}{space 3}-5.182962
{txt}        /cut3 {c |}{col 15}{res}{space 2}-31.57166{col 27}{space 2} 14.85127{col 55}{space 4}-60.67961{col 68}{space 3} -2.46371
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 5159.5278.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}    718.92
{txt}Log pseudolikelihood = {res}-2104.7958{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.7808078{col 27}{space 2} .2167623{col 38}{space 1}   -3.60{col 47}{space 3}0.000{col 55}{space 4}-1.205654{col 68}{space 3}-.3559614
{txt}{space 7}imfgdp {c |}{col 15}{res}{space 2} .0122874{col 27}{space 2} .0348864{col 38}{space 1}    0.35{col 47}{space 3}0.725{col 55}{space 4}-.0560888{col 68}{space 3} .0806636
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0222865{col 27}{space 2} .0077857{col 38}{space 1}    2.86{col 47}{space 3}0.004{col 55}{space 4} .0070268{col 68}{space 3} .0375462
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0007299{col 27}{space 2} .0063094{col 38}{space 1}   -0.12{col 47}{space 3}0.908{col 55}{space 4} -.013096{col 68}{space 3} .0116363
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0415678{col 27}{space 2} .0422056{col 38}{space 1}    0.98{col 47}{space 3}0.325{col 55}{space 4}-.0411537{col 68}{space 3} .1242893
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2} -.352839{col 27}{space 2} .1838587{col 38}{space 1}   -1.92{col 47}{space 3}0.055{col 55}{space 4}-.7131954{col 68}{space 3} .0075174
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2421823{col 27}{space 2} .1052278{col 38}{space 1}    2.30{col 47}{space 3}0.021{col 55}{space 4} .0359397{col 68}{space 3} .4484249
{txt}lntotalfempop {c |}{col 15}{res}{space 2} -.089062{col 27}{space 2} .0276118{col 38}{space 1}   -3.23{col 47}{space 3}0.001{col 55}{space 4}-.1431801{col 68}{space 3}-.0349438
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2851464{col 27}{space 2} .1052434{col 38}{space 1}   -2.71{col 47}{space 3}0.007{col 55}{space 4}-.4914197{col 68}{space 3}-.0788732
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.0423588{col 27}{space 2} .2124802{col 38}{space 1}   -0.20{col 47}{space 3}0.842{col 55}{space 4}-.4588122{col 68}{space 3} .3740947
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.091963{col 27}{space 2} .5534395{col 38}{space 1}   -3.78{col 47}{space 3}0.000{col 55}{space 4}-3.176684{col 68}{space 3}-1.007241
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0096553{col 27}{space 2} .0010572{col 38}{space 1}   -9.13{col 47}{space 3}0.000{col 55}{space 4}-.0117274{col 68}{space 3}-.0075831
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.362064{col 27}{space 2} .2759524{col 38}{space 1}    4.94{col 47}{space 3}0.000{col 55}{space 4} .8212072{col 68}{space 3} 1.902921
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.119795{col 27}{space 2}  .342955{col 38}{space 1}    9.10{col 47}{space 3}0.000{col 55}{space 4} 2.447616{col 68}{space 3} 3.791974
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.499375{col 27}{space 2} .5083744{col 38}{space 1}    8.85{col 47}{space 3}0.000{col 55}{space 4} 3.502979{col 68}{space 3}  5.49577
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1961765{col 27}{space 2} .0332404{col 38}{space 1}   -5.90{col 47}{space 3}0.000{col 55}{space 4}-.2613265{col 68}{space 3}-.1310265
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2}  .002281{col 27}{space 2} .0076012{col 38}{space 1}    0.30{col 47}{space 3}0.764{col 55}{space 4} -.012617{col 68}{space 3}  .017179
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2543728{col 27}{space 2} .1149132{col 38}{space 1}   -2.21{col 47}{space 3}0.027{col 55}{space 4}-.4795986{col 68}{space 3} -.029147
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000173{col 27}{space 2} .0000187{col 38}{space 1}    0.92{col 47}{space 3}0.355{col 55}{space 4}-.0000194{col 68}{space 3}  .000054
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2} -.051308{col 27}{space 2} .1077334{col 38}{space 1}   -0.48{col 47}{space 3}0.634{col 55}{space 4}-.2624616{col 68}{space 3} .1598456
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0187846{col 27}{space 2} .0225623{col 38}{space 1}   -0.83{col 47}{space 3}0.405{col 55}{space 4}-.0630058{col 68}{space 3} .0254367
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .2388277{col 27}{space 2} .1254171{col 38}{space 1}    1.90{col 47}{space 3}0.057{col 55}{space 4}-.0069853{col 68}{space 3} .4846406
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8719005{col 27}{space 2} .2612224{col 38}{space 1}    3.34{col 47}{space 3}0.001{col 55}{space 4}  .359914{col 68}{space 3} 1.383887
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0838136{col 27}{space 2}  .184057{col 38}{space 1}    0.46{col 47}{space 3}0.649{col 55}{space 4}-.2769314{col 68}{space 3} .4445587
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4603515{col 27}{space 2} .2076345{col 38}{space 1}    2.22{col 47}{space 3}0.027{col 55}{space 4} .0533953{col 68}{space 3} .8673077
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9499181{col 27}{space 2} .2943931{col 38}{space 1}    3.23{col 47}{space 3}0.001{col 55}{space 4} .3729181{col 68}{space 3} 1.526918
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.1862861{col 27}{space 2} .3371321{col 38}{space 1}   -0.55{col 47}{space 3}0.581{col 55}{space 4}-.8470529{col 68}{space 3} .4744807
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6342924{col 27}{space 2} .2228035{col 38}{space 1}    2.85{col 47}{space 3}0.004{col 55}{space 4} .1976055{col 68}{space 3} 1.070979
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1499818{col 27}{space 2} .2532901{col 38}{space 1}    0.59{col 47}{space 3}0.554{col 55}{space 4}-.3464576{col 68}{space 3} .6464213
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.029013{col 27}{space 2} 1.013191{col 38}{space 1}    1.02{col 47}{space 3}0.310{col 55}{space 4}-.9568059{col 68}{space 3} 3.014831
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .4916356{col 27}{space 2}  .154822{col 38}{space 1}    3.18{col 47}{space 3}0.001{col 55}{space 4} .1881901{col 68}{space 3} .7950812
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2}-23.21067{col 27}{space 2} 1.883101{col 38}{space 1}  -12.33{col 47}{space 3}0.000{col 55}{space 4}-26.90148{col 68}{space 3}-19.51986
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2}-20.10439{col 27}{space 2}  1.87446{col 38}{space 1}  -10.73{col 47}{space 3}0.000{col 55}{space 4}-23.77826{col 68}{space 3}-16.43051
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2}-17.52025{col 27}{space 2} 1.951887{col 38}{space 1}   -8.98{col 47}{space 3}0.000{col 55}{space 4}-21.34588{col 68}{space 3}-13.69462
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .4555137{col 27}{space 2} .1226976{col 55}{space 4} .1859995{col 68}{space 3} .6612779
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Table III WOPOL Rights
. cmp(wopol = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagwopolglobe trend lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res}-658.12306
{txt}Iteration 2:   log likelihood = {res}-602.84786
{txt}Iteration 3:   log likelihood = {res}-599.79751
{txt}Iteration 4:   log likelihood = {res}-599.77711
{txt}Iteration 5:   log likelihood = {res}-599.77711

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}14{txt}){col 67}= {res}   1468.80
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-599.77711{txt}{col 51}Pseudo R2{col 67}= {res}    0.5505

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0689728{col 27}{space 2}  .087406{col 38}{space 1}   -0.79{col 47}{space 3}0.430{col 55}{space 4}-.2402854{col 68}{space 3} .1023397
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0124029{col 27}{space 2} .0072533{col 38}{space 1}    1.71{col 47}{space 3}0.087{col 55}{space 4}-.0018133{col 68}{space 3}  .026619
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0356431{col 27}{space 2} .0089225{col 38}{space 1}   -3.99{col 47}{space 3}0.000{col 55}{space 4}-.0531309{col 68}{space 3}-.0181553
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0314285{col 27}{space 2} .0484298{col 38}{space 1}    0.65{col 47}{space 3}0.516{col 55}{space 4}-.0634922{col 68}{space 3} .1263493
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0581183{col 27}{space 2} .2589547{col 38}{space 1}   -0.22{col 47}{space 3}0.822{col 55}{space 4}-.5656603{col 68}{space 3} .4494236
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2}  .311761{col 27}{space 2} .1039889{col 38}{space 1}    3.00{col 47}{space 3}0.003{col 55}{space 4} .1079464{col 68}{space 3} .5155756
{txt}lntotalfempop {c |}{col 15}{res}{space 2} .0004788{col 27}{space 2} .0303827{col 38}{space 1}    0.02{col 47}{space 3}0.987{col 55}{space 4}-.0590701{col 68}{space 3} .0600278
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1357368{col 27}{space 2} .1037308{col 38}{space 1}   -1.31{col 47}{space 3}0.191{col 55}{space 4}-.3390455{col 68}{space 3} .0675718
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.3623252{col 27}{space 2} .1253338{col 38}{space 1}   -2.89{col 47}{space 3}0.004{col 55}{space 4}-.6079749{col 68}{space 3}-.1166754
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.180758{col 27}{space 2} .8507443{col 38}{space 1}   -1.39{col 47}{space 3}0.165{col 55}{space 4}-2.848186{col 68}{space 3} .4866706
{txt}{space 8}trend {c |}{col 15}{res}{space 2}  .041754{col 27}{space 2} .0194757{col 38}{space 1}    2.14{col 47}{space 3}0.032{col 55}{space 4} .0035824{col 68}{space 3} .0799256
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.196279{col 27}{space 2} .1727016{col 38}{space 1}    6.93{col 47}{space 3}0.000{col 55}{space 4} .8577898{col 68}{space 3} 1.534767
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.546057{col 27}{space 2} .1858336{col 38}{space 1}   19.08{col 47}{space 3}0.000{col 55}{space 4}  3.18183{col 68}{space 3} 3.910284
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2}  6.79425{col 27}{space 2} .4839961{col 38}{space 1}   14.04{col 47}{space 3}0.000{col 55}{space 4} 5.845635{col 68}{space 3} 7.742865
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 81.16248{col 27}{space 2} 37.54102{col 55}{space 4} 7.583431{col 68}{space 3} 154.7415
{txt}        /cut2 {c |}{col 15}{res}{space 2} 83.59884{col 27}{space 2} 37.54799{col 55}{space 4} 10.00615{col 68}{space 3} 157.1915
{txt}        /cut3 {c |}{col 15}{res}{space 2} 87.79408{col 27}{space 2} 37.55771{col 55}{space 4} 14.18232{col 68}{space 3} 161.4058
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3432.6721.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}14{txt}){col 67}= {res}  23901.29
{txt}Log pseudolikelihood = {res}-1885.6366{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.3578838{col 27}{space 2}  .210929{col 38}{space 1}   -1.70{col 47}{space 3}0.090{col 55}{space 4}-.7712971{col 68}{space 3} .0555295
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0130997{col 27}{space 2} .0065513{col 38}{space 1}    2.00{col 47}{space 3}0.046{col 55}{space 4} .0002594{col 68}{space 3}   .02594
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0396567{col 27}{space 2} .0100407{col 38}{space 1}   -3.95{col 47}{space 3}0.000{col 55}{space 4}-.0593362{col 68}{space 3}-.0199772
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0123955{col 27}{space 2} .0464531{col 38}{space 1}    0.27{col 47}{space 3}0.790{col 55}{space 4} -.078651{col 68}{space 3} .1034419
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0439752{col 27}{space 2} .2911411{col 38}{space 1}   -0.15{col 47}{space 3}0.880{col 55}{space 4}-.6146012{col 68}{space 3} .5266508
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2974541{col 27}{space 2} .0981593{col 38}{space 1}    3.03{col 47}{space 3}0.002{col 55}{space 4} .1050654{col 68}{space 3} .4898428
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0030064{col 27}{space 2} .0371984{col 38}{space 1}   -0.08{col 47}{space 3}0.936{col 55}{space 4}-.0759139{col 68}{space 3} .0699011
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1713883{col 27}{space 2} .1059509{col 38}{space 1}   -1.62{col 47}{space 3}0.106{col 55}{space 4}-.3790482{col 68}{space 3} .0362716
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.4086243{col 27}{space 2} .1316107{col 38}{space 1}   -3.10{col 47}{space 3}0.002{col 55}{space 4}-.6665765{col 68}{space 3}-.1506722
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.284143{col 27}{space 2} .4010271{col 38}{space 1}   -3.20{col 47}{space 3}0.001{col 55}{space 4}-2.070142{col 68}{space 3}-.4981443
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0474903{col 27}{space 2} .0005916{col 38}{space 1}   80.27{col 47}{space 3}0.000{col 55}{space 4} .0463307{col 68}{space 3} .0486498
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2}  1.17598{col 27}{space 2} .3238317{col 38}{space 1}    3.63{col 47}{space 3}0.000{col 55}{space 4} .5412818{col 68}{space 3} 1.810679
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.502164{col 27}{space 2} .3829804{col 38}{space 1}    9.14{col 47}{space 3}0.000{col 55}{space 4} 2.751536{col 68}{space 3} 4.252792
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.705216{col 27}{space 2} .5641252{col 38}{space 1}   11.89{col 47}{space 3}0.000{col 55}{space 4} 5.599551{col 68}{space 3} 7.810881
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1966497{col 27}{space 2} .0334336{col 38}{space 1}   -5.88{col 47}{space 3}0.000{col 55}{space 4}-.2621783{col 68}{space 3} -.131121
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0017849{col 27}{space 2} .0076706{col 38}{space 1}    0.23{col 47}{space 3}0.816{col 55}{space 4}-.0132491{col 68}{space 3} .0168189
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2477589{col 27}{space 2} .1153618{col 38}{space 1}   -2.15{col 47}{space 3}0.032{col 55}{space 4}-.4738638{col 68}{space 3}-.0216539
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000141{col 27}{space 2} .0000199{col 38}{space 1}    0.71{col 47}{space 3}0.478{col 55}{space 4}-.0000249{col 68}{space 3} .0000532
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0416948{col 27}{space 2} .1068306{col 38}{space 1}   -0.39{col 47}{space 3}0.696{col 55}{space 4}-.2510788{col 68}{space 3} .1676892
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0158145{col 27}{space 2} .0224196{col 38}{space 1}   -0.71{col 47}{space 3}0.481{col 55}{space 4}-.0597562{col 68}{space 3} .0281272
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .1953543{col 27}{space 2} .1213441{col 38}{space 1}    1.61{col 47}{space 3}0.107{col 55}{space 4}-.0424757{col 68}{space 3} .4331843
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8399288{col 27}{space 2} .2744593{col 38}{space 1}    3.06{col 47}{space 3}0.002{col 55}{space 4} .3019985{col 68}{space 3} 1.377859
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0404886{col 27}{space 2}  .187955{col 38}{space 1}    0.22{col 47}{space 3}0.829{col 55}{space 4}-.3278966{col 68}{space 3} .4088737
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4641947{col 27}{space 2} .2120344{col 38}{space 1}    2.19{col 47}{space 3}0.029{col 55}{space 4} .0486148{col 68}{space 3} .8797745
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9332811{col 27}{space 2}  .301881{col 38}{space 1}    3.09{col 47}{space 3}0.002{col 55}{space 4} .3416052{col 68}{space 3} 1.524957
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.2114546{col 27}{space 2} .3491055{col 38}{space 1}   -0.61{col 47}{space 3}0.545{col 55}{space 4}-.8956888{col 68}{space 3} .4727795
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6123668{col 27}{space 2} .2233886{col 38}{space 1}    2.74{col 47}{space 3}0.006{col 55}{space 4} .1745333{col 68}{space 3}   1.0502
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1232111{col 27}{space 2} .2598986{col 38}{space 1}    0.47{col 47}{space 3}0.635{col 55}{space 4}-.3861809{col 68}{space 3} .6326031
{txt}{space 8}_cons {c |}{col 15}{res}{space 2}  .992011{col 27}{space 2} 1.024201{col 38}{space 1}    0.97{col 47}{space 3}0.333{col 55}{space 4}-1.015386{col 68}{space 3} 2.999408
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1926823{col 27}{space 2} .1246652{col 38}{space 1}    1.55{col 47}{space 3}0.122{col 55}{space 4}-.0516571{col 68}{space 3} .4370217
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 92.13373{col 27}{space 2} .7323586{col 38}{space 1}  125.80{col 47}{space 3}0.000{col 55}{space 4} 90.69834{col 68}{space 3} 93.56913
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 94.54699{col 27}{space 2} .7130115{col 38}{space 1}  132.60{col 47}{space 3}0.000{col 55}{space 4} 93.14951{col 68}{space 3} 95.94446
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 98.69949{col 27}{space 2} .7086272{col 38}{space 1}  139.28{col 47}{space 3}0.000{col 55}{space 4} 97.31061{col 68}{space 3} 100.0884
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1903327{col 27}{space 2} .1201491{col 55}{space 4}-.0516112{col 68}{space 3} .4111727
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wopol = imfdummy imfpolity polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagwopolglobe trend lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res}-657.62134
{txt}Iteration 2:   log likelihood = {res}-601.99517
{txt}Iteration 3:   log likelihood = {res}-598.89295
{txt}Iteration 4:   log likelihood = {res}-598.87194
{txt}Iteration 5:   log likelihood = {res}-598.87194

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}   1470.61
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-598.87194{txt}{col 51}Pseudo R2{col 67}= {res}    0.5511

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2} .1397348{col 27}{space 2} .1783464{col 38}{space 1}    0.78{col 47}{space 3}0.433{col 55}{space 4}-.2098179{col 68}{space 3} .4892874
{txt}{space 4}imfpolity {c |}{col 15}{res}{space 2}-.0176251{col 27}{space 2} .0131151{col 38}{space 1}   -1.34{col 47}{space 3}0.179{col 55}{space 4}-.0433303{col 68}{space 3}   .00808
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0193205{col 27}{space 2}  .008901{col 38}{space 1}    2.17{col 47}{space 3}0.030{col 55}{space 4} .0018748{col 68}{space 3} .0367662
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0352574{col 27}{space 2} .0089372{col 38}{space 1}   -3.95{col 47}{space 3}0.000{col 55}{space 4}-.0527741{col 68}{space 3}-.0177408
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0279184{col 27}{space 2} .0484994{col 38}{space 1}    0.58{col 47}{space 3}0.565{col 55}{space 4}-.0671387{col 68}{space 3} .1229755
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0586856{col 27}{space 2} .2591309{col 38}{space 1}   -0.23{col 47}{space 3}0.821{col 55}{space 4}-.5665728{col 68}{space 3} .4492017
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .3113167{col 27}{space 2} .1039623{col 38}{space 1}    2.99{col 47}{space 3}0.003{col 55}{space 4} .1075542{col 68}{space 3} .5150791
{txt}lntotalfempop {c |}{col 15}{res}{space 2} .0010125{col 27}{space 2} .0303805{col 38}{space 1}    0.03{col 47}{space 3}0.973{col 55}{space 4}-.0585322{col 68}{space 3} .0605571
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1518501{col 27}{space 2} .1044929{col 38}{space 1}   -1.45{col 47}{space 3}0.146{col 55}{space 4}-.3566525{col 68}{space 3} .0529523
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.3350384{col 27}{space 2} .1269566{col 38}{space 1}   -2.64{col 47}{space 3}0.008{col 55}{space 4}-.5838688{col 68}{space 3}-.0862081
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.217096{col 27}{space 2} .8516688{col 38}{space 1}   -1.43{col 47}{space 3}0.153{col 55}{space 4}-2.886337{col 68}{space 3} .4521437
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0433132{col 27}{space 2}  .019521{col 38}{space 1}    2.22{col 47}{space 3}0.026{col 55}{space 4} .0050529{col 68}{space 3} .0815736
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.170843{col 27}{space 2} .1737714{col 38}{space 1}    6.74{col 47}{space 3}0.000{col 55}{space 4} .8302576{col 68}{space 3} 1.511429
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.530268{col 27}{space 2} .1862091{col 38}{space 1}   18.96{col 47}{space 3}0.000{col 55}{space 4} 3.165305{col 68}{space 3} 3.895231
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.743646{col 27}{space 2} .4847356{col 38}{space 1}   13.91{col 47}{space 3}0.000{col 55}{space 4} 5.793582{col 68}{space 3} 7.693711
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 84.26211{col 27}{space 2} 37.63212{col 55}{space 4}  10.5045{col 68}{space 3} 158.0197
{txt}        /cut2 {c |}{col 15}{res}{space 2}  86.7001{col 27}{space 2} 37.63908{col 55}{space 4} 12.92885{col 68}{space 3} 160.4714
{txt}        /cut3 {c |}{col 15}{res}{space 2} 90.90392{col 27}{space 2} 37.64949{col 55}{space 4} 17.11229{col 68}{space 3} 164.6956
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3628.4036.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}  23636.18
{txt}Log pseudolikelihood = {res} -1884.731{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.1511737{col 27}{space 2} .2827902{col 38}{space 1}   -0.53{col 47}{space 3}0.593{col 55}{space 4}-.7054324{col 68}{space 3}  .403085
{txt}{space 4}imfpolity {c |}{col 15}{res}{space 2}-.0174505{col 27}{space 2} .0143869{col 38}{space 1}   -1.21{col 47}{space 3}0.225{col 55}{space 4}-.0456482{col 68}{space 3} .0107473
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0199458{col 27}{space 2} .0083418{col 38}{space 1}    2.39{col 47}{space 3}0.017{col 55}{space 4}  .003596{col 68}{space 3} .0362955
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0392668{col 27}{space 2} .0101254{col 38}{space 1}   -3.88{col 47}{space 3}0.000{col 55}{space 4}-.0591122{col 68}{space 3}-.0194213
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0088856{col 27}{space 2} .0461567{col 38}{space 1}    0.19{col 47}{space 3}0.847{col 55}{space 4}-.0815798{col 68}{space 3}  .099351
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0444487{col 27}{space 2} .2960191{col 38}{space 1}   -0.15{col 47}{space 3}0.881{col 55}{space 4}-.6246355{col 68}{space 3} .5357381
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2969696{col 27}{space 2} .0994956{col 38}{space 1}    2.98{col 47}{space 3}0.003{col 55}{space 4} .1019617{col 68}{space 3} .4919775
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0025068{col 27}{space 2} .0374452{col 38}{space 1}   -0.07{col 47}{space 3}0.947{col 55}{space 4} -.075898{col 68}{space 3} .0708843
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1873022{col 27}{space 2} .1062676{col 38}{space 1}   -1.76{col 47}{space 3}0.078{col 55}{space 4}-.3955828{col 68}{space 3} .0209784
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.3816558{col 27}{space 2} .1360107{col 38}{space 1}   -2.81{col 47}{space 3}0.005{col 55}{space 4} -.648232{col 68}{space 3}-.1150797
{txt}lagwopolglobe {c |}{col 15}{res}{space 2} -1.31963{col 27}{space 2} .4050085{col 38}{space 1}   -3.26{col 47}{space 3}0.001{col 55}{space 4}-2.113432{col 68}{space 3}-.5258279
{txt}{space 8}trend {c |}{col 15}{res}{space 2}  .049015{col 27}{space 2} .0005611{col 38}{space 1}   87.36{col 47}{space 3}0.000{col 55}{space 4} .0479153{col 68}{space 3} .0501147
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.150741{col 27}{space 2} .3248673{col 38}{space 1}    3.54{col 47}{space 3}0.000{col 55}{space 4}  .514013{col 68}{space 3} 1.787469
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.486405{col 27}{space 2} .3833043{col 38}{space 1}    9.10{col 47}{space 3}0.000{col 55}{space 4} 2.735143{col 68}{space 3} 4.237668
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.654708{col 27}{space 2} .5669696{col 38}{space 1}   11.74{col 47}{space 3}0.000{col 55}{space 4} 5.543469{col 68}{space 3} 7.765948
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1964836{col 27}{space 2} .0333833{col 38}{space 1}   -5.89{col 47}{space 3}0.000{col 55}{space 4}-.2619136{col 68}{space 3}-.1310536
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0017785{col 27}{space 2} .0076654{col 38}{space 1}    0.23{col 47}{space 3}0.817{col 55}{space 4}-.0132455{col 68}{space 3} .0168025
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2475591{col 27}{space 2} .1154164{col 38}{space 1}   -2.14{col 47}{space 3}0.032{col 55}{space 4}-.4737712{col 68}{space 3}-.0213471
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000142{col 27}{space 2} .0000199{col 38}{space 1}    0.71{col 47}{space 3}0.476{col 55}{space 4}-.0000248{col 68}{space 3} .0000532
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0414929{col 27}{space 2} .1068608{col 38}{space 1}   -0.39{col 47}{space 3}0.698{col 55}{space 4}-.2509362{col 68}{space 3} .1679504
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0158256{col 27}{space 2} .0224181{col 38}{space 1}   -0.71{col 47}{space 3}0.480{col 55}{space 4}-.0597643{col 68}{space 3}  .028113
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .1950109{col 27}{space 2} .1213146{col 38}{space 1}    1.61{col 47}{space 3}0.108{col 55}{space 4}-.0427613{col 68}{space 3} .4327831
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8397141{col 27}{space 2}  .274517{col 38}{space 1}    3.06{col 47}{space 3}0.002{col 55}{space 4} .3016705{col 68}{space 3} 1.377758
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0411795{col 27}{space 2} .1880023{col 38}{space 1}    0.22{col 47}{space 3}0.827{col 55}{space 4}-.3272983{col 68}{space 3} .4096572
{txt}{space 7}colfra {c |}{col 15}{res}{space 2}  .464686{col 27}{space 2} .2119544{col 38}{space 1}    2.19{col 47}{space 3}0.028{col 55}{space 4}  .049263{col 68}{space 3} .8801089
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9327808{col 27}{space 2} .3017871{col 38}{space 1}    3.09{col 47}{space 3}0.002{col 55}{space 4} .3412888{col 68}{space 3} 1.524273
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.2123144{col 27}{space 2} .3488618{col 38}{space 1}   -0.61{col 47}{space 3}0.543{col 55}{space 4} -.896071{col 68}{space 3} .4714422
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6120708{col 27}{space 2} .2232655{col 38}{space 1}    2.74{col 47}{space 3}0.006{col 55}{space 4} .1744785{col 68}{space 3} 1.049663
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1221348{col 27}{space 2} .2596393{col 38}{space 1}    0.47{col 47}{space 3}0.638{col 55}{space 4} -.386749{col 68}{space 3} .6310185
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .9905409{col 27}{space 2} 1.024283{col 38}{space 1}    0.97{col 47}{space 3}0.334{col 55}{space 4}-1.017017{col 68}{space 3} 2.998098
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1926518{col 27}{space 2} .1253046{col 38}{space 1}    1.54{col 47}{space 3}0.124{col 55}{space 4}-.0529407{col 68}{space 3} .4382443
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 95.16498{col 27}{space 2} .7007697{col 38}{space 1}  135.80{col 47}{space 3}0.000{col 55}{space 4} 93.79149{col 68}{space 3} 96.53846
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 97.57947{col 27}{space 2} .6949597{col 38}{space 1}  140.41{col 47}{space 3}0.000{col 55}{space 4} 96.21737{col 68}{space 3} 98.94156
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 101.7404{col 27}{space 2} .7092593{col 38}{space 1}  143.45{col 47}{space 3}0.000{col 55}{space 4} 100.3503{col 68}{space 3} 103.1305
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1903033{col 27}{space 2} .1207667{col 55}{space 4}-.0528913{col 68}{space 3} .4121881
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wopol = imfdummy imfgdp polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagwopolglobe trend lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res}-657.68451
{txt}Iteration 2:   log likelihood = {res}-602.03086
{txt}Iteration 3:   log likelihood = {res}-598.89077
{txt}Iteration 4:   log likelihood = {res}-598.86832
{txt}Iteration 5:   log likelihood = {res}-598.86832

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}   1470.62
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-598.86832{txt}{col 51}Pseudo R2{col 67}= {res}    0.5511

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.1514758{col 27}{space 2} .1067575{col 38}{space 1}   -1.42{col 47}{space 3}0.156{col 55}{space 4}-.3607167{col 68}{space 3} .0577651
{txt}{space 7}imfgdp {c |}{col 15}{res}{space 2} .0473636{col 27}{space 2} .0353332{col 38}{space 1}    1.34{col 47}{space 3}0.180{col 55}{space 4}-.0218882{col 68}{space 3} .1166153
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0104325{col 27}{space 2} .0074006{col 38}{space 1}    1.41{col 47}{space 3}0.159{col 55}{space 4}-.0040723{col 68}{space 3} .0249373
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0380703{col 27}{space 2} .0092759{col 38}{space 1}   -4.10{col 47}{space 3}0.000{col 55}{space 4}-.0562507{col 68}{space 3}-.0198899
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0280909{col 27}{space 2} .0485778{col 38}{space 1}    0.58{col 47}{space 3}0.563{col 55}{space 4}-.0671199{col 68}{space 3} .1233017
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0525722{col 27}{space 2} .2592047{col 38}{space 1}   -0.20{col 47}{space 3}0.839{col 55}{space 4} -.560604{col 68}{space 3} .4554596
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2991093{col 27}{space 2} .1044555{col 38}{space 1}    2.86{col 47}{space 3}0.004{col 55}{space 4} .0943802{col 68}{space 3} .5038384
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0028028{col 27}{space 2} .0305061{col 38}{space 1}   -0.09{col 47}{space 3}0.927{col 55}{space 4}-.0625936{col 68}{space 3}  .056988
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1298683{col 27}{space 2} .1037848{col 38}{space 1}   -1.25{col 47}{space 3}0.211{col 55}{space 4}-.3332827{col 68}{space 3} .0735461
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.3843991{col 27}{space 2} .1264735{col 38}{space 1}   -3.04{col 47}{space 3}0.002{col 55}{space 4}-.6322825{col 68}{space 3}-.1365156
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.198429{col 27}{space 2} .8511551{col 38}{space 1}   -1.41{col 47}{space 3}0.159{col 55}{space 4}-2.866662{col 68}{space 3} .4698043
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0438386{col 27}{space 2}  .019546{col 38}{space 1}    2.24{col 47}{space 3}0.025{col 55}{space 4}  .005529{col 68}{space 3} .0821481
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.191218{col 27}{space 2} .1727666{col 38}{space 1}    6.89{col 47}{space 3}0.000{col 55}{space 4} .8526016{col 68}{space 3} 1.529834
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.535176{col 27}{space 2} .1860817{col 38}{space 1}   19.00{col 47}{space 3}0.000{col 55}{space 4} 3.170463{col 68}{space 3}  3.89989
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.786427{col 27}{space 2} .4845235{col 38}{space 1}   14.01{col 47}{space 3}0.000{col 55}{space 4} 5.836779{col 68}{space 3} 7.736076
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 85.16403{col 27}{space 2} 37.67581{col 55}{space 4}  11.3208{col 68}{space 3} 159.0073
{txt}        /cut2 {c |}{col 15}{res}{space 2} 87.60326{col 27}{space 2} 37.68302{col 55}{space 4}  13.7459{col 68}{space 3} 161.4606
{txt}        /cut3 {c |}{col 15}{res}{space 2} 91.80005{col 27}{space 2} 37.69315{col 55}{space 4} 17.92283{col 68}{space 3} 165.6773
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3528.931.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}  22718.91
{txt}Log pseudolikelihood = {res}-1885.2142{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.3462051{col 27}{space 2} .2055838{col 38}{space 1}   -1.68{col 47}{space 3}0.092{col 55}{space 4}-.7491421{col 68}{space 3} .0567318
{txt}{space 7}imfgdp {c |}{col 15}{res}{space 2} .0344353{col 27}{space 2} .0269159{col 38}{space 1}    1.28{col 47}{space 3}0.201{col 55}{space 4}-.0183189{col 68}{space 3} .0871894
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0114953{col 27}{space 2} .0066999{col 38}{space 1}    1.72{col 47}{space 3}0.086{col 55}{space 4}-.0016362{col 68}{space 3} .0246269
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0404908{col 27}{space 2} .0100379{col 38}{space 1}   -4.03{col 47}{space 3}0.000{col 55}{space 4}-.0601646{col 68}{space 3}-.0208169
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0146328{col 27}{space 2}  .045993{col 38}{space 1}    0.32{col 47}{space 3}0.750{col 55}{space 4}-.0755119{col 68}{space 3} .1047774
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0444334{col 27}{space 2} .2904098{col 38}{space 1}   -0.15{col 47}{space 3}0.878{col 55}{space 4}-.6136261{col 68}{space 3} .5247593
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2920507{col 27}{space 2} .0990325{col 38}{space 1}    2.95{col 47}{space 3}0.003{col 55}{space 4} .0979507{col 68}{space 3} .4861508
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0045479{col 27}{space 2} .0372974{col 38}{space 1}   -0.12{col 47}{space 3}0.903{col 55}{space 4}-.0776494{col 68}{space 3} .0685536
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1586137{col 27}{space 2}   .10671{col 38}{space 1}   -1.49{col 47}{space 3}0.137{col 55}{space 4}-.3677614{col 68}{space 3} .0505341
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.4139555{col 27}{space 2} .1320512{col 38}{space 1}   -3.13{col 47}{space 3}0.002{col 55}{space 4}-.6727711{col 68}{space 3}-.1551399
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.290077{col 27}{space 2} .4037778{col 38}{space 1}   -3.20{col 47}{space 3}0.001{col 55}{space 4}-2.081467{col 68}{space 3} -.498687
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0480818{col 27}{space 2}  .000539{col 38}{space 1}   89.21{col 47}{space 3}0.000{col 55}{space 4} .0470255{col 68}{space 3} .0491382
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2}  1.18062{col 27}{space 2} .3229381{col 38}{space 1}    3.66{col 47}{space 3}0.000{col 55}{space 4}  .547673{col 68}{space 3} 1.813567
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.513082{col 27}{space 2}  .379841{col 38}{space 1}    9.25{col 47}{space 3}0.000{col 55}{space 4} 2.768607{col 68}{space 3} 4.257556
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.736458{col 27}{space 2}  .555638{col 38}{space 1}   12.12{col 47}{space 3}0.000{col 55}{space 4} 5.647428{col 68}{space 3} 7.825489
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2} -.195888{col 27}{space 2} .0335191{col 38}{space 1}   -5.84{col 47}{space 3}0.000{col 55}{space 4}-.2615842{col 68}{space 3}-.1301918
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0017581{col 27}{space 2} .0076695{col 38}{space 1}    0.23{col 47}{space 3}0.819{col 55}{space 4}-.0132738{col 68}{space 3}   .01679
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2} -.247178{col 27}{space 2} .1155079{col 38}{space 1}   -2.14{col 47}{space 3}0.032{col 55}{space 4}-.4735694{col 68}{space 3}-.0207866
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000143{col 27}{space 2}   .00002{col 38}{space 1}    0.71{col 47}{space 3}0.475{col 55}{space 4}-.0000248{col 68}{space 3} .0000534
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0415415{col 27}{space 2} .1068927{col 38}{space 1}   -0.39{col 47}{space 3}0.698{col 55}{space 4}-.2510474{col 68}{space 3} .1679643
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0158425{col 27}{space 2} .0224522{col 38}{space 1}   -0.71{col 47}{space 3}0.480{col 55}{space 4} -.059848{col 68}{space 3} .0281629
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .1935458{col 27}{space 2} .1215363{col 38}{space 1}    1.59{col 47}{space 3}0.111{col 55}{space 4}-.0446609{col 68}{space 3} .4317526
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8421262{col 27}{space 2}  .274109{col 38}{space 1}    3.07{col 47}{space 3}0.002{col 55}{space 4} .3048824{col 68}{space 3}  1.37937
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0391007{col 27}{space 2} .1883085{col 38}{space 1}    0.21{col 47}{space 3}0.836{col 55}{space 4}-.3299773{col 68}{space 3} .4081786
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4635859{col 27}{space 2} .2123639{col 38}{space 1}    2.18{col 47}{space 3}0.029{col 55}{space 4} .0473603{col 68}{space 3} .8798115
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9318575{col 27}{space 2}  .301956{col 38}{space 1}    3.09{col 47}{space 3}0.002{col 55}{space 4} .3400346{col 68}{space 3} 1.523681
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.2136773{col 27}{space 2} .3483371{col 38}{space 1}   -0.61{col 47}{space 3}0.540{col 55}{space 4}-.8964055{col 68}{space 3}  .469051
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2}  .610922{col 27}{space 2} .2232436{col 38}{space 1}    2.74{col 47}{space 3}0.006{col 55}{space 4} .1733726{col 68}{space 3} 1.048471
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1188541{col 27}{space 2}  .259432{col 38}{space 1}    0.46{col 47}{space 3}0.647{col 55}{space 4}-.3896233{col 68}{space 3} .6273315
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .9908001{col 27}{space 2} 1.025549{col 38}{space 1}    0.97{col 47}{space 3}0.334{col 55}{space 4} -1.01924{col 68}{space 3}  3.00084
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1444121{col 27}{space 2} .1251762{col 38}{space 1}    1.15{col 47}{space 3}0.249{col 55}{space 4}-.1009287{col 68}{space 3} .3897529
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 93.28526{col 27}{space 2} .6956026{col 38}{space 1}  134.11{col 47}{space 3}0.000{col 55}{space 4}  91.9219{col 68}{space 3} 94.64861
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 95.71096{col 27}{space 2} .6989989{col 38}{space 1}  136.93{col 47}{space 3}0.000{col 55}{space 4} 94.34095{col 68}{space 3} 97.08098
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 99.88354{col 27}{space 2} .7205432{col 38}{space 1}  138.62{col 47}{space 3}0.000{col 55}{space 4}  98.4713{col 68}{space 3} 101.2958
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1434165{col 27}{space 2} .1226015{col 55}{space 4}-.1005874{col 68}{space 3} .3711471
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. * Table II Substantive Effects
. probit wecondummy imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme  lagweconglobe trend, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-355.13833}  
Iteration 1:{space 3}log pseudolikelihood = {res:-291.31581}  
Iteration 2:{space 3}log pseudolikelihood = {res:-285.79091}  
Iteration 3:{space 3}log pseudolikelihood = {res:-285.75477}  
Iteration 4:{space 3}log pseudolikelihood = {res:-285.75477}  
{res}
{txt}Probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}Wald chi2({res}11{txt}){col 67}= {res}     76.66
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-285.75477{txt}{col 51}Pseudo R2{col 67}= {res}    0.1954

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}   wecondummy{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.2439845{col 27}{space 2} .1223114{col 38}{space 1}   -1.99{col 47}{space 3}0.046{col 55}{space 4}-.4837105{col 68}{space 3}-.0042586
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0318254{col 27}{space 2}  .010262{col 38}{space 1}    3.10{col 47}{space 3}0.002{col 55}{space 4} .0117124{col 68}{space 3} .0519385
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0211825{col 27}{space 2} .0094314{col 38}{space 1}   -2.25{col 47}{space 3}0.025{col 55}{space 4}-.0396676{col 68}{space 3}-.0026973
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .3090306{col 27}{space 2} .0633316{col 38}{space 1}    4.88{col 47}{space 3}0.000{col 55}{space 4} .1849029{col 68}{space 3} .4331583
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.6633497{col 27}{space 2} .3627244{col 38}{space 1}   -1.83{col 47}{space 3}0.067{col 55}{space 4}-1.374276{col 68}{space 3} .0475772
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .7263171{col 27}{space 2} .1528207{col 38}{space 1}    4.75{col 47}{space 3}0.000{col 55}{space 4}  .426794{col 68}{space 3}  1.02584
{txt}lntotalfempop {c |}{col 15}{res}{space 2} -.207168{col 27}{space 2} .0422882{col 38}{space 1}   -4.90{col 47}{space 3}0.000{col 55}{space 4}-.2900513{col 68}{space 3}-.1242847
{txt}civilconflict {c |}{col 15}{res}{space 2}-.4220901{col 27}{space 2} .1192273{col 38}{space 1}   -3.54{col 47}{space 3}0.000{col 55}{space 4}-.6557714{col 68}{space 3}-.1884088
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}  .038174{col 27}{space 2} .1539645{col 38}{space 1}    0.25{col 47}{space 3}0.804{col 55}{space 4} -.263591{col 68}{space 3} .3399389
{txt}lagweconglobe {c |}{col 15}{res}{space 2}  -1.2536{col 27}{space 2} .7566415{col 38}{space 1}   -1.66{col 47}{space 3}0.098{col 55}{space 4} -2.73659{col 68}{space 3} .2293904
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0334007{col 27}{space 2} .0124849{col 38}{space 1}   -2.68{col 47}{space 3}0.007{col 55}{space 4}-.0578706{col 68}{space 3}-.0089308
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 70.81488{col 27}{space 2}  24.6666{col 38}{space 1}    2.87{col 47}{space 3}0.004{col 55}{space 4} 22.46924{col 68}{space 3} 119.1605
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. * IMF impact
. prvalue, x(imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9395{col 32}{txt}[{res} 0.9063{txt},{res}{col 44} 0.9727{txt}]
  Pr(y=0|x):{res}{col 22} 0.0605{col 32}{txt}[{res} 0.0273{txt},{res}{col 44} 0.0937{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523     .07920145             0     15.557197             0             0     1.1681511     1993.1276
{txt}
{com}. 
. prvalue, x(imfdummy=1 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9043{col 32}{txt}[{res} 0.8579{txt},{res}{col 44} 0.9508{txt}]
  Pr(y=0|x):{res}{col 22} 0.0957{col 32}{txt}[{res} 0.0492{txt},{res}{col 44} 0.1421{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           1     12.336963     3.4236755     5.5895523     .07920145             0     15.557197             0             0     1.1681511     1993.1276
{txt}
{com}. **OTHER CONTROLS
. * Democracy Impact 1 Std. below to 1 std. above
. prvalue, x( polity2=5.8 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9103{col 32}{txt}[{res} 0.8688{txt},{res}{col 44} 0.9518{txt}]
  Pr(y=0|x):{res}{col 22} 0.0897{col 32}{txt}[{res} 0.0482{txt},{res}{col 44} 0.1312{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0           5.8     3.4236755     5.5895523     .07920145             0     15.557197             0             0     1.1681511     1993.1276
{txt}
{com}. 
. prvalue, x( polity2=17.8 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9577{col 32}{txt}[{res} 0.9274{txt},{res}{col 44} 0.9880{txt}]
  Pr(y=0|x):{res}{col 22} 0.0423{col 32}{txt}[{res} 0.0120{txt},{res}{col 44} 0.0726{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0          17.8     3.4236755     5.5895523     .07920145             0     15.557197             0             0     1.1681511     1993.1276
{txt}
{com}. 
. * Differend Economic Lib 1 Std. below to 1 std. above
. prvalue, x( Dindexipo=-0.09 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9518{col 32}{txt}[{res} 0.9216{txt},{res}{col 44} 0.9821{txt}]
  Pr(y=0|x):{res}{col 22} 0.0482{col 32}{txt}[{res} 0.0179{txt},{res}{col 44} 0.0784{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523          -.09             0     15.557197             0             0     1.1681511     1993.1276
{txt}
{com}. 
. prvalue, x( Dindexipo=0.24 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9256{col 32}{txt}[{res} 0.8835{txt},{res}{col 44} 0.9678{txt}]
  Pr(y=0|x):{res}{col 22} 0.0744{col 32}{txt}[{res} 0.0322{txt},{res}{col 44} 0.1165{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523           .24             0     15.557197             0             0     1.1681511     1993.1276
{txt}
{com}. 
. * Cedaw Dummy
. prvalue, x( imfdummy=0 cedawdummy=1 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9886{col 32}{txt}[{res} 0.9807{txt},{res}{col 44} 0.9965{txt}]
  Pr(y=0|x):{res}{col 22} 0.0114{col 32}{txt}[{res} 0.0035{txt},{res}{col 44} 0.0193{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523     .07920145             1     15.557197             0             0     1.1681511     1993.1276
{txt}
{com}. 
. * Female Pop 1 Std. below to 1 std. above
. prvalue, x( lntotalfempop=13.8 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9722{col 32}{txt}[{res} 0.9509{txt},{res}{col 44} 0.9935{txt}]
  Pr(y=0|x):{res}{col 22} 0.0278{col 32}{txt}[{res} 0.0065{txt},{res}{col 44} 0.0491{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523     .07920145             0          13.8             0             0     1.1681511     1993.1276
{txt}
{com}. 
. prvalue, x( lntotalfempop=16.8 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9020{col 32}{txt}[{res} 0.8537{txt},{res}{col 44} 0.9503{txt}]
  Pr(y=0|x):{res}{col 22} 0.0980{col 32}{txt}[{res} 0.0497{txt},{res}{col 44} 0.1463{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523     .07920145             0          16.8             0             0     1.1681511     1993.1276
{txt}
{com}. 
. * Civil Wars
. prvalue, x(imfdummy=0 cedawdummy=0 civilconflict=1 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.8704{col 32}{txt}[{res} 0.8054{txt},{res}{col 44} 0.9355{txt}]
  Pr(y=0|x):{res}{col 22} 0.1296{col 32}{txt}[{res} 0.0645{txt},{res}{col 44} 0.1946{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523     .07920145             0     15.557197             1             0     1.1681511     1993.1276
{txt}
{com}. 
. * Global Women's Rights 1 Std. below to 1 std. above
. prvalue, x( lagweconglobe=1.09 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9504{col 32}{txt}[{res} 0.9187{txt},{res}{col 44} 0.9821{txt}]
  Pr(y=0|x):{res}{col 22} 0.0496{col 32}{txt}[{res} 0.0179{txt},{res}{col 44} 0.0813{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523     .07920145             0     15.557197             0             0          1.09     1993.1276
{txt}
{com}. 
. prvalue, x( lagweconglobe=1.233 imfdummy=0 cedawdummy=0 civilconflict=0 nafrme=0) rest(mean)

{res}probit{txt}: Predictions for {res}wecondummy

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.9291{col 32}{txt}[{res} 0.8904{txt},{res}{col 44} 0.9679{txt}]
  Pr(y=0|x):{res}{col 22} 0.0709{col 32}{txt}[{res} 0.0321{txt},{res}{col 44} 0.1096{txt}]

        imfdummy       polity2       gdpecon      indexipo     Dindexipo    cedawdummy  lntotalfem~p  civilconfl~t        nafrme  lagwecongl~e         trend
x=  {res}           0     12.336963     3.4236755     5.5895523     .07920145             0     15.557197             0             0         1.233     1993.1276
{txt}
{com}. 
. 
. * TABLE AI
. cmp(wecon = imfsba imfsfaorprfg polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagwopolglobe trend lwecon1 lwecon2 lwecon3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res}-855.74911
{txt}Iteration 2:   log likelihood = {res}-832.22299
{txt}Iteration 3:   log likelihood = {res}-831.56782
{txt}Iteration 4:   log likelihood = {res} -831.5662

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}    897.99
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -831.5662{txt}{col 51}Pseudo R2{col 67}= {res}    0.3506

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}imfsba {c |}{col 15}{res}{space 2} .0074069{col 27}{space 2} .0878576{col 38}{space 1}    0.08{col 47}{space 3}0.933{col 55}{space 4}-.1647909{col 68}{space 3} .1796046
{txt}{space 1}imfsfaorprfg {c |}{col 15}{res}{space 2}-.2079535{col 27}{space 2} .1014174{col 38}{space 1}   -2.05{col 47}{space 3}0.040{col 55}{space 4} -.406728{col 68}{space 3} -.009179
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0204635{col 27}{space 2} .0065075{col 38}{space 1}    3.14{col 47}{space 3}0.002{col 55}{space 4}  .007709{col 68}{space 3}  .033218
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0069713{col 27}{space 2} .0062729{col 38}{space 1}    1.11{col 47}{space 3}0.266{col 55}{space 4}-.0053234{col 68}{space 3}  .019266
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0785882{col 27}{space 2} .0416004{col 38}{space 1}    1.89{col 47}{space 3}0.059{col 55}{space 4}-.0029471{col 68}{space 3} .1601235
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2} -.360631{col 27}{space 2} .2098593{col 38}{space 1}   -1.72{col 47}{space 3}0.086{col 55}{space 4}-.7719477{col 68}{space 3} .0506857
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2860817{col 27}{space 2} .0979322{col 38}{space 1}    2.92{col 47}{space 3}0.003{col 55}{space 4} .0941382{col 68}{space 3} .4780252
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0905854{col 27}{space 2} .0257626{col 38}{space 1}   -3.52{col 47}{space 3}0.000{col 55}{space 4}-.1410792{col 68}{space 3}-.0400916
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2151008{col 27}{space 2} .0931842{col 38}{space 1}   -2.31{col 47}{space 3}0.021{col 55}{space 4}-.3977384{col 68}{space 3}-.0324632
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} .0229614{col 27}{space 2} .1220107{col 38}{space 1}    0.19{col 47}{space 3}0.851{col 55}{space 4}-.2161752{col 68}{space 3} .2620981
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-.9149499{col 27}{space 2}  .757104{col 38}{space 1}   -1.21{col 47}{space 3}0.227{col 55}{space 4}-2.398847{col 68}{space 3} .5689467
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0028027{col 27}{space 2} .0178978{col 38}{space 1}   -0.16{col 47}{space 3}0.876{col 55}{space 4}-.0378817{col 68}{space 3} .0322764
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.399429{col 27}{space 2} .1347184{col 38}{space 1}   10.39{col 47}{space 3}0.000{col 55}{space 4} 1.135386{col 68}{space 3} 1.663472
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.230341{col 27}{space 2} .1581407{col 38}{space 1}   20.43{col 47}{space 3}0.000{col 55}{space 4} 2.920391{col 68}{space 3} 3.540291
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.670319{col 27}{space 2} .4294908{col 38}{space 1}   10.87{col 47}{space 3}0.000{col 55}{space 4} 3.828532{col 68}{space 3} 5.512105
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2}-8.125827{col 27}{space 2} 34.52048{col 55}{space 4}-75.78472{col 68}{space 3} 59.53306
{txt}        /cut2 {c |}{col 15}{res}{space 2}-4.878687{col 27}{space 2} 34.51902{col 55}{space 4}-72.53473{col 68}{space 3} 62.77735
{txt}        /cut3 {c |}{col 15}{res}{space 2}-2.182994{col 27}{space 2} 34.52085{col 55}{space 4}-69.84261{col 68}{space 3} 65.47662
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3504.2158.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}    371.41
{txt}Log pseudolikelihood = {res}-2114.1012{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 7}imfsba {c |}{col 15}{res}{space 2}-.4918567{col 27}{space 2} .2287521{col 38}{space 1}   -2.15{col 47}{space 3}0.032{col 55}{space 4}-.9402026{col 68}{space 3}-.0435108
{txt}{space 1}imfsfaorprfg {c |}{col 15}{res}{space 2}-.6077488{col 27}{space 2} .1911752{col 38}{space 1}   -3.18{col 47}{space 3}0.001{col 55}{space 4}-.9824453{col 68}{space 3}-.2330523
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0218199{col 27}{space 2} .0079107{col 38}{space 1}    2.76{col 47}{space 3}0.006{col 55}{space 4} .0063152{col 68}{space 3} .0373245
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0018302{col 27}{space 2} .0067612{col 38}{space 1}    0.27{col 47}{space 3}0.787{col 55}{space 4}-.0114215{col 68}{space 3}  .015082
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0499815{col 27}{space 2} .0461161{col 38}{space 1}    1.08{col 47}{space 3}0.278{col 55}{space 4}-.0404043{col 68}{space 3} .1403674
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2} -.349049{col 27}{space 2} .1853238{col 38}{space 1}   -1.88{col 47}{space 3}0.060{col 55}{space 4} -.712277{col 68}{space 3} .0141789
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2}  .252444{col 27}{space 2} .1183907{col 38}{space 1}    2.13{col 47}{space 3}0.033{col 55}{space 4} .0204025{col 68}{space 3} .4844855
{txt}lntotalfempop {c |}{col 15}{res}{space 2} -.092001{col 27}{space 2} .0286129{col 38}{space 1}   -3.22{col 47}{space 3}0.001{col 55}{space 4}-.1480813{col 68}{space 3}-.0359207
{txt}civilconflict {c |}{col 15}{res}{space 2} -.275517{col 27}{space 2}  .106427{col 38}{space 1}   -2.59{col 47}{space 3}0.010{col 55}{space 4}  -.48411{col 68}{space 3} -.066924
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.0376602{col 27}{space 2} .2132934{col 38}{space 1}   -0.18{col 47}{space 3}0.860{col 55}{space 4}-.4557077{col 68}{space 3} .3803873
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-.9809655{col 27}{space 2} .3270156{col 38}{space 1}   -3.00{col 47}{space 3}0.003{col 55}{space 4}-1.621904{col 68}{space 3}-.3400267
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0026672{col 27}{space 2} .0004141{col 38}{space 1}    6.44{col 47}{space 3}0.000{col 55}{space 4} .0018556{col 68}{space 3} .0034789
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.353922{col 27}{space 2} .2828659{col 38}{space 1}    4.79{col 47}{space 3}0.000{col 55}{space 4} .7995153{col 68}{space 3} 1.908329
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.123271{col 27}{space 2} .3316106{col 38}{space 1}    9.42{col 47}{space 3}0.000{col 55}{space 4} 2.473326{col 68}{space 3} 3.773216
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.506867{col 27}{space 2} .5074863{col 38}{space 1}    8.88{col 47}{space 3}0.000{col 55}{space 4} 3.512212{col 68}{space 3} 5.501522
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1974388{col 27}{space 2} .0337656{col 38}{space 1}   -5.85{col 47}{space 3}0.000{col 55}{space 4}-.2636182{col 68}{space 3}-.1312594
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0020684{col 27}{space 2} .0076491{col 38}{space 1}    0.27{col 47}{space 3}0.787{col 55}{space 4}-.0129235{col 68}{space 3} .0170603
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2524762{col 27}{space 2} .1154868{col 38}{space 1}   -2.19{col 47}{space 3}0.029{col 55}{space 4}-.4788261{col 68}{space 3}-.0261263
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2}  .000017{col 27}{space 2} .0000193{col 38}{space 1}    0.88{col 47}{space 3}0.378{col 55}{space 4}-.0000208{col 68}{space 3} .0000548
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2} -.049361{col 27}{space 2}  .107996{col 38}{space 1}   -0.46{col 47}{space 3}0.648{col 55}{space 4}-.2610293{col 68}{space 3} .1623072
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0177148{col 27}{space 2}  .022588{col 38}{space 1}   -0.78{col 47}{space 3}0.433{col 55}{space 4}-.0619866{col 68}{space 3} .0265569
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .2217249{col 27}{space 2} .1251433{col 38}{space 1}    1.77{col 47}{space 3}0.076{col 55}{space 4}-.0235515{col 68}{space 3} .4670012
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8695922{col 27}{space 2} .2644846{col 38}{space 1}    3.29{col 47}{space 3}0.001{col 55}{space 4}  .351212{col 68}{space 3} 1.387973
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2}  .071048{col 27}{space 2} .1863327{col 38}{space 1}    0.38{col 47}{space 3}0.703{col 55}{space 4}-.2941574{col 68}{space 3} .4362533
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4636079{col 27}{space 2} .2100987{col 38}{space 1}    2.21{col 47}{space 3}0.027{col 55}{space 4} .0518221{col 68}{space 3} .8753937
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9431014{col 27}{space 2} .2969852{col 38}{space 1}    3.18{col 47}{space 3}0.001{col 55}{space 4} .3610212{col 68}{space 3} 1.525182
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.2015675{col 27}{space 2} .3395137{col 38}{space 1}   -0.59{col 47}{space 3}0.553{col 55}{space 4}-.8670021{col 68}{space 3} .4638672
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6246851{col 27}{space 2}  .222562{col 38}{space 1}    2.81{col 47}{space 3}0.005{col 55}{space 4} .1884716{col 68}{space 3} 1.060899
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1317423{col 27}{space 2}   .25365{col 38}{space 1}    0.52{col 47}{space 3}0.603{col 55}{space 4}-.3654027{col 68}{space 3} .6288872
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.028106{col 27}{space 2} 1.020238{col 38}{space 1}    1.01{col 47}{space 3}0.314{col 55}{space 4}-.9715234{col 68}{space 3} 3.027736
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .3539093{col 27}{space 2} .1439208{col 38}{space 1}    2.46{col 47}{space 3}0.014{col 55}{space 4} .0718298{col 68}{space 3} .6359889
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 2.274014{col 27}{space 2} .6520077{col 38}{space 1}    3.49{col 47}{space 3}0.000{col 55}{space 4}  .996103{col 68}{space 3} 3.551926
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 5.436906{col 27}{space 2} .6314238{col 38}{space 1}    8.61{col 47}{space 3}0.000{col 55}{space 4} 4.199338{col 68}{space 3} 6.674474
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 8.064368{col 27}{space 2} .7170254{col 38}{space 1}   11.25{col 47}{space 3}0.000{col 55}{space 4} 6.659024{col 68}{space 3} 9.469712
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2}  .339838{col 27}{space 2} .1272994{col 55}{space 4} .0717065{col 68}{space 3} .5621622
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wopol = imfsba imfsfaorprfg polity2 gdpecon indexipo Dindexipo cedawdummy  lntotalfempop civilconflict nafrme lagwopolglobe trend lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res}-657.84555
{txt}Iteration 2:   log likelihood = {res}-602.20707
{txt}Iteration 3:   log likelihood = {res}-599.05937
{txt}Iteration 4:   log likelihood = {res}-599.03685
{txt}Iteration 5:   log likelihood = {res}-599.03685

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}15{txt}){col 67}= {res}   1470.28
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-599.03685{txt}{col 51}Pseudo R2{col 67}= {res}    0.5510

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}imfsba {c |}{col 15}{res}{space 2}-.0025645{col 27}{space 2} .1010973{col 38}{space 1}   -0.03{col 47}{space 3}0.980{col 55}{space 4}-.2007115{col 68}{space 3} .1955826
{txt}{space 1}imfsfaorprfg {c |}{col 15}{res}{space 2} -.173638{col 27}{space 2} .1202314{col 38}{space 1}   -1.44{col 47}{space 3}0.149{col 55}{space 4}-.4092873{col 68}{space 3} .0620112
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0111374{col 27}{space 2} .0073282{col 38}{space 1}    1.52{col 47}{space 3}0.129{col 55}{space 4}-.0032256{col 68}{space 3} .0255004
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0367533{col 27}{space 2} .0090637{col 38}{space 1}   -4.06{col 47}{space 3}0.000{col 55}{space 4}-.0545178{col 68}{space 3}-.0189888
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0259995{col 27}{space 2} .0487254{col 38}{space 1}    0.53{col 47}{space 3}0.594{col 55}{space 4}-.0695006{col 68}{space 3} .1214996
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0330444{col 27}{space 2} .2599147{col 38}{space 1}   -0.13{col 47}{space 3}0.899{col 55}{space 4}-.5424678{col 68}{space 3}  .476379
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2}  .308946{col 27}{space 2} .1039521{col 38}{space 1}    2.97{col 47}{space 3}0.003{col 55}{space 4} .1052036{col 68}{space 3} .5126884
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0026067{col 27}{space 2} .0305145{col 38}{space 1}   -0.09{col 47}{space 3}0.932{col 55}{space 4} -.062414{col 68}{space 3} .0572007
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1351912{col 27}{space 2} .1036996{col 38}{space 1}   -1.30{col 47}{space 3}0.192{col 55}{space 4}-.3384386{col 68}{space 3} .0680562
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.3929549{col 27}{space 2} .1279251{col 38}{space 1}   -3.07{col 47}{space 3}0.002{col 55}{space 4}-.6436835{col 68}{space 3}-.1422263
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.161342{col 27}{space 2} .8519351{col 38}{space 1}   -1.36{col 47}{space 3}0.173{col 55}{space 4}-2.831104{col 68}{space 3} .5084202
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0446823{col 27}{space 2} .0196962{col 38}{space 1}    2.27{col 47}{space 3}0.023{col 55}{space 4} .0060784{col 68}{space 3} .0832862
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.189195{col 27}{space 2} .1729629{col 38}{space 1}    6.88{col 47}{space 3}0.000{col 55}{space 4} .8501936{col 68}{space 3} 1.528196
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.538079{col 27}{space 2} .1861797{col 38}{space 1}   19.00{col 47}{space 3}0.000{col 55}{space 4} 3.173174{col 68}{space 3} 3.902984
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.763489{col 27}{space 2} .4842767{col 38}{space 1}   13.97{col 47}{space 3}0.000{col 55}{space 4} 5.814324{col 68}{space 3} 7.712654
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 86.91025{col 27}{space 2}  37.9808{col 55}{space 4} 12.46926{col 68}{space 3} 161.3512
{txt}        /cut2 {c |}{col 15}{res}{space 2} 89.35048{col 27}{space 2} 37.98832{col 55}{space 4} 14.89474{col 68}{space 3} 163.8062
{txt}        /cut3 {c |}{col 15}{res}{space 2} 93.54946{col 27}{space 2} 37.99867{col 55}{space 4} 19.07343{col 68}{space 3} 168.0255
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3512.7553.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}  23838.27
{txt}Log pseudolikelihood = {res}-1885.2981{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 7}imfsba {c |}{col 15}{res}{space 2}-.1889576{col 27}{space 2} .1910568{col 38}{space 1}   -0.99{col 47}{space 3}0.323{col 55}{space 4} -.563422{col 68}{space 3} .1855067
{txt}{space 1}imfsfaorprfg {c |}{col 15}{res}{space 2}-.3264651{col 27}{space 2} .1839588{col 38}{space 1}   -1.77{col 47}{space 3}0.076{col 55}{space 4}-.6870178{col 68}{space 3} .0340876
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0116668{col 27}{space 2} .0064868{col 38}{space 1}    1.80{col 47}{space 3}0.072{col 55}{space 4}-.0010471{col 68}{space 3} .0243808
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0390606{col 27}{space 2} .0096494{col 38}{space 1}   -4.05{col 47}{space 3}0.000{col 55}{space 4}-.0579731{col 68}{space 3}-.0201481
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0139469{col 27}{space 2} .0475241{col 38}{space 1}    0.29{col 47}{space 3}0.769{col 55}{space 4}-.0791987{col 68}{space 3} .1070925
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2} -.028772{col 27}{space 2} .2947301{col 38}{space 1}   -0.10{col 47}{space 3}0.922{col 55}{space 4}-.6064324{col 68}{space 3} .5488884
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2964254{col 27}{space 2} .0984586{col 38}{space 1}    3.01{col 47}{space 3}0.003{col 55}{space 4} .1034501{col 68}{space 3} .4894006
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0042583{col 27}{space 2} .0375079{col 38}{space 1}   -0.11{col 47}{space 3}0.910{col 55}{space 4}-.0777725{col 68}{space 3} .0692558
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1602047{col 27}{space 2} .1040466{col 38}{space 1}   -1.54{col 47}{space 3}0.124{col 55}{space 4}-.3641323{col 68}{space 3} .0437228
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} -.419717{col 27}{space 2} .1367642{col 38}{space 1}   -3.07{col 47}{space 3}0.002{col 55}{space 4}-.6877698{col 68}{space 3}-.1516642
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.226611{col 27}{space 2} .4487732{col 38}{space 1}   -2.73{col 47}{space 3}0.006{col 55}{space 4} -2.10619{col 68}{space 3}-.3470315
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0477506{col 27}{space 2} .0005498{col 38}{space 1}   86.85{col 47}{space 3}0.000{col 55}{space 4}  .046673{col 68}{space 3} .0488282
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.179583{col 27}{space 2} .3206358{col 38}{space 1}    3.68{col 47}{space 3}0.000{col 55}{space 4} .5511487{col 68}{space 3} 1.808018
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.521652{col 27}{space 2} .3733297{col 38}{space 1}    9.43{col 47}{space 3}0.000{col 55}{space 4} 2.789939{col 68}{space 3} 4.253365
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.733889{col 27}{space 2} .5451148{col 38}{space 1}   12.35{col 47}{space 3}0.000{col 55}{space 4} 5.665483{col 68}{space 3} 7.802294
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1961773{col 27}{space 2} .0334549{col 38}{space 1}   -5.86{col 47}{space 3}0.000{col 55}{space 4}-.2617476{col 68}{space 3}-.1306069
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0017545{col 27}{space 2} .0076672{col 38}{space 1}    0.23{col 47}{space 3}0.819{col 55}{space 4}-.0132729{col 68}{space 3}  .016782
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2468665{col 27}{space 2} .1155459{col 38}{space 1}   -2.14{col 47}{space 3}0.033{col 55}{space 4}-.4733322{col 68}{space 3}-.0204008
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000143{col 27}{space 2}   .00002{col 38}{space 1}    0.72{col 47}{space 3}0.474{col 55}{space 4}-.0000248{col 68}{space 3} .0000534
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0412772{col 27}{space 2} .1069006{col 38}{space 1}   -0.39{col 47}{space 3}0.699{col 55}{space 4}-.2507986{col 68}{space 3} .1682441
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} -.015771{col 27}{space 2} .0224559{col 38}{space 1}   -0.70{col 47}{space 3}0.482{col 55}{space 4}-.0597838{col 68}{space 3} .0282418
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2}  .192433{col 27}{space 2} .1221107{col 38}{space 1}    1.58{col 47}{space 3}0.115{col 55}{space 4}-.0468996{col 68}{space 3} .4317656
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8412761{col 27}{space 2}  .274062{col 38}{space 1}    3.07{col 47}{space 3}0.002{col 55}{space 4} .3041245{col 68}{space 3} 1.378428
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0391459{col 27}{space 2} .1883756{col 38}{space 1}    0.21{col 47}{space 3}0.835{col 55}{space 4}-.3300635{col 68}{space 3} .4083552
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4635979{col 27}{space 2} .2124175{col 38}{space 1}    2.18{col 47}{space 3}0.029{col 55}{space 4} .0472672{col 68}{space 3} .8799286
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9312253{col 27}{space 2} .3019827{col 38}{space 1}    3.08{col 47}{space 3}0.002{col 55}{space 4}   .33935{col 68}{space 3} 1.523101
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2} -.213309{col 27}{space 2} .3481015{col 38}{space 1}   -0.61{col 47}{space 3}0.540{col 55}{space 4}-.8955755{col 68}{space 3} .4689575
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6093227{col 27}{space 2}  .223247{col 38}{space 1}    2.73{col 47}{space 3}0.006{col 55}{space 4} .1717666{col 68}{space 3} 1.046879
{txt}{space 9}asia {c |}{col 15}{res}{space 2}  .116279{col 27}{space 2} .2584381{col 38}{space 1}    0.45{col 47}{space 3}0.653{col 55}{space 4}-.3902503{col 68}{space 3} .6228084
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .9898872{col 27}{space 2} 1.025768{col 38}{space 1}    0.97{col 47}{space 3}0.335{col 55}{space 4}-1.020582{col 68}{space 3} 3.000356
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1271991{col 27}{space 2}  .111433{col 38}{space 1}    1.14{col 47}{space 3}0.254{col 55}{space 4}-.0912056{col 68}{space 3} .3456038
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 92.74643{col 27}{space 2} .6922188{col 38}{space 1}  133.98{col 47}{space 3}0.000{col 55}{space 4}  91.3897{col 68}{space 3} 94.10315
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 95.17519{col 27}{space 2} .6850662{col 38}{space 1}  138.93{col 47}{space 3}0.000{col 55}{space 4} 93.83248{col 68}{space 3}  96.5179
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 99.35655{col 27}{space 2} .6961333{col 38}{space 1}  142.73{col 47}{space 3}0.000{col 55}{space 4} 97.99216{col 68}{space 3} 100.7209
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1265175{col 27}{space 2} .1096493{col 55}{space 4}-.0909536{col 68}{space 3}  .332471
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *Summary Statistics TABLE AII
. cmp(wopol = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagwopolglobe trend lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res}-658.12306
{txt}Iteration 2:   log likelihood = {res}-602.84786
{txt}Iteration 3:   log likelihood = {res}-599.79751
{txt}Iteration 4:   log likelihood = {res}-599.77711
{txt}Iteration 5:   log likelihood = {res}-599.77711

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}14{txt}){col 67}= {res}   1468.80
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-599.77711{txt}{col 51}Pseudo R2{col 67}= {res}    0.5505

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0689728{col 27}{space 2}  .087406{col 38}{space 1}   -0.79{col 47}{space 3}0.430{col 55}{space 4}-.2402854{col 68}{space 3} .1023397
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0124029{col 27}{space 2} .0072533{col 38}{space 1}    1.71{col 47}{space 3}0.087{col 55}{space 4}-.0018133{col 68}{space 3}  .026619
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0356431{col 27}{space 2} .0089225{col 38}{space 1}   -3.99{col 47}{space 3}0.000{col 55}{space 4}-.0531309{col 68}{space 3}-.0181553
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0314285{col 27}{space 2} .0484298{col 38}{space 1}    0.65{col 47}{space 3}0.516{col 55}{space 4}-.0634922{col 68}{space 3} .1263493
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0581183{col 27}{space 2} .2589547{col 38}{space 1}   -0.22{col 47}{space 3}0.822{col 55}{space 4}-.5656603{col 68}{space 3} .4494236
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2}  .311761{col 27}{space 2} .1039889{col 38}{space 1}    3.00{col 47}{space 3}0.003{col 55}{space 4} .1079464{col 68}{space 3} .5155756
{txt}lntotalfempop {c |}{col 15}{res}{space 2} .0004788{col 27}{space 2} .0303827{col 38}{space 1}    0.02{col 47}{space 3}0.987{col 55}{space 4}-.0590701{col 68}{space 3} .0600278
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1357368{col 27}{space 2} .1037308{col 38}{space 1}   -1.31{col 47}{space 3}0.191{col 55}{space 4}-.3390455{col 68}{space 3} .0675718
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.3623252{col 27}{space 2} .1253338{col 38}{space 1}   -2.89{col 47}{space 3}0.004{col 55}{space 4}-.6079749{col 68}{space 3}-.1166754
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.180758{col 27}{space 2} .8507443{col 38}{space 1}   -1.39{col 47}{space 3}0.165{col 55}{space 4}-2.848186{col 68}{space 3} .4866706
{txt}{space 8}trend {c |}{col 15}{res}{space 2}  .041754{col 27}{space 2} .0194757{col 38}{space 1}    2.14{col 47}{space 3}0.032{col 55}{space 4} .0035824{col 68}{space 3} .0799256
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.196279{col 27}{space 2} .1727016{col 38}{space 1}    6.93{col 47}{space 3}0.000{col 55}{space 4} .8577898{col 68}{space 3} 1.534767
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.546057{col 27}{space 2} .1858336{col 38}{space 1}   19.08{col 47}{space 3}0.000{col 55}{space 4}  3.18183{col 68}{space 3} 3.910284
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2}  6.79425{col 27}{space 2} .4839961{col 38}{space 1}   14.04{col 47}{space 3}0.000{col 55}{space 4} 5.845635{col 68}{space 3} 7.742865
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 81.16248{col 27}{space 2} 37.54102{col 55}{space 4} 7.583431{col 68}{space 3} 154.7415
{txt}        /cut2 {c |}{col 15}{res}{space 2} 83.59884{col 27}{space 2} 37.54799{col 55}{space 4} 10.00615{col 68}{space 3} 157.1915
{txt}        /cut3 {c |}{col 15}{res}{space 2} 87.79408{col 27}{space 2} 37.55771{col 55}{space 4} 14.18232{col 68}{space 3} 161.4058
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3432.6721.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}14{txt}){col 67}= {res}  23901.29
{txt}Log pseudolikelihood = {res}-1885.6366{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.3578838{col 27}{space 2}  .210929{col 38}{space 1}   -1.70{col 47}{space 3}0.090{col 55}{space 4}-.7712971{col 68}{space 3} .0555295
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0130997{col 27}{space 2} .0065513{col 38}{space 1}    2.00{col 47}{space 3}0.046{col 55}{space 4} .0002594{col 68}{space 3}   .02594
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0396567{col 27}{space 2} .0100407{col 38}{space 1}   -3.95{col 47}{space 3}0.000{col 55}{space 4}-.0593362{col 68}{space 3}-.0199772
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0123955{col 27}{space 2} .0464531{col 38}{space 1}    0.27{col 47}{space 3}0.790{col 55}{space 4} -.078651{col 68}{space 3} .1034419
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0439752{col 27}{space 2} .2911411{col 38}{space 1}   -0.15{col 47}{space 3}0.880{col 55}{space 4}-.6146012{col 68}{space 3} .5266508
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2974541{col 27}{space 2} .0981593{col 38}{space 1}    3.03{col 47}{space 3}0.002{col 55}{space 4} .1050654{col 68}{space 3} .4898428
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0030064{col 27}{space 2} .0371984{col 38}{space 1}   -0.08{col 47}{space 3}0.936{col 55}{space 4}-.0759139{col 68}{space 3} .0699011
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1713883{col 27}{space 2} .1059509{col 38}{space 1}   -1.62{col 47}{space 3}0.106{col 55}{space 4}-.3790482{col 68}{space 3} .0362716
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.4086243{col 27}{space 2} .1316107{col 38}{space 1}   -3.10{col 47}{space 3}0.002{col 55}{space 4}-.6665765{col 68}{space 3}-.1506722
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.284143{col 27}{space 2} .4010271{col 38}{space 1}   -3.20{col 47}{space 3}0.001{col 55}{space 4}-2.070142{col 68}{space 3}-.4981443
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0474903{col 27}{space 2} .0005916{col 38}{space 1}   80.27{col 47}{space 3}0.000{col 55}{space 4} .0463307{col 68}{space 3} .0486498
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2}  1.17598{col 27}{space 2} .3238317{col 38}{space 1}    3.63{col 47}{space 3}0.000{col 55}{space 4} .5412818{col 68}{space 3} 1.810679
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.502164{col 27}{space 2} .3829804{col 38}{space 1}    9.14{col 47}{space 3}0.000{col 55}{space 4} 2.751536{col 68}{space 3} 4.252792
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.705216{col 27}{space 2} .5641252{col 38}{space 1}   11.89{col 47}{space 3}0.000{col 55}{space 4} 5.599551{col 68}{space 3} 7.810881
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1966497{col 27}{space 2} .0334336{col 38}{space 1}   -5.88{col 47}{space 3}0.000{col 55}{space 4}-.2621783{col 68}{space 3} -.131121
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0017849{col 27}{space 2} .0076706{col 38}{space 1}    0.23{col 47}{space 3}0.816{col 55}{space 4}-.0132491{col 68}{space 3} .0168189
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2477589{col 27}{space 2} .1153618{col 38}{space 1}   -2.15{col 47}{space 3}0.032{col 55}{space 4}-.4738638{col 68}{space 3}-.0216539
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000141{col 27}{space 2} .0000199{col 38}{space 1}    0.71{col 47}{space 3}0.478{col 55}{space 4}-.0000249{col 68}{space 3} .0000532
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0416948{col 27}{space 2} .1068306{col 38}{space 1}   -0.39{col 47}{space 3}0.696{col 55}{space 4}-.2510788{col 68}{space 3} .1676892
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0158145{col 27}{space 2} .0224196{col 38}{space 1}   -0.71{col 47}{space 3}0.481{col 55}{space 4}-.0597562{col 68}{space 3} .0281272
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .1953543{col 27}{space 2} .1213441{col 38}{space 1}    1.61{col 47}{space 3}0.107{col 55}{space 4}-.0424757{col 68}{space 3} .4331843
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8399288{col 27}{space 2} .2744593{col 38}{space 1}    3.06{col 47}{space 3}0.002{col 55}{space 4} .3019985{col 68}{space 3} 1.377859
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0404886{col 27}{space 2}  .187955{col 38}{space 1}    0.22{col 47}{space 3}0.829{col 55}{space 4}-.3278966{col 68}{space 3} .4088737
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4641947{col 27}{space 2} .2120344{col 38}{space 1}    2.19{col 47}{space 3}0.029{col 55}{space 4} .0486148{col 68}{space 3} .8797745
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9332811{col 27}{space 2}  .301881{col 38}{space 1}    3.09{col 47}{space 3}0.002{col 55}{space 4} .3416052{col 68}{space 3} 1.524957
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.2114546{col 27}{space 2} .3491055{col 38}{space 1}   -0.61{col 47}{space 3}0.545{col 55}{space 4}-.8956888{col 68}{space 3} .4727795
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6123668{col 27}{space 2} .2233886{col 38}{space 1}    2.74{col 47}{space 3}0.006{col 55}{space 4} .1745333{col 68}{space 3}   1.0502
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1232111{col 27}{space 2} .2598986{col 38}{space 1}    0.47{col 47}{space 3}0.635{col 55}{space 4}-.3861809{col 68}{space 3} .6326031
{txt}{space 8}_cons {c |}{col 15}{res}{space 2}  .992011{col 27}{space 2} 1.024201{col 38}{space 1}    0.97{col 47}{space 3}0.333{col 55}{space 4}-1.015386{col 68}{space 3} 2.999408
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1926823{col 27}{space 2} .1246652{col 38}{space 1}    1.55{col 47}{space 3}0.122{col 55}{space 4}-.0516571{col 68}{space 3} .4370217
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 92.13373{col 27}{space 2} .7323586{col 38}{space 1}  125.80{col 47}{space 3}0.000{col 55}{space 4} 90.69834{col 68}{space 3} 93.56913
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 94.54699{col 27}{space 2} .7130115{col 38}{space 1}  132.60{col 47}{space 3}0.000{col 55}{space 4} 93.14951{col 68}{space 3} 95.94446
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 98.69949{col 27}{space 2} .7086272{col 38}{space 1}  139.28{col 47}{space 3}0.000{col 55}{space 4} 97.31061{col 68}{space 3} 100.0884
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1903327{col 27}{space 2} .1201491{col 55}{space 4}-.0516112{col 68}{space 3} .4111727
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. sum wopol imfdummy imfgdp polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict trend lagwopolglobe gdpgrowth currency exchrate coldwar usalliance colbrit colfra nafrme eeurop lamerica ssafrica asia if e(sample)

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 7}wopol {c |}{res}      2250    1.614222    .6245122          0          3
{txt}{space 4}imfdummy {c |}{res}      2289    .3748362    .4841864          0          1
{txt}{space 6}imfgdp {c |}{res}      2289    .5421102    1.324912          0   14.42879
{txt}{space 5}polity2 {c |}{res}      2289    11.09174    6.818409          1         21
{txt}{space 5}gdpecon {c |}{res}      2289    3.055945    5.879183   .1017755   70.24655
{txt}{hline 13}{c +}{hline 56}
{space 4}indexipo {c |}{res}      1798    5.574266     1.12665          2        8.9
{txt}{space 3}Dindexipo {c |}{res}      1782    .0752637    .1687737       -1.1         .7
{txt}{space 2}cedawdummy {c |}{res}      2266    .7144748    .4517639          0          1
{txt}lntotalfem~p {c |}{res}      2289     15.3118    1.527816   11.95666   20.24922
{txt}civilconfl~t {c |}{res}      2276    .2144112    .4105035          0          1
{txt}{hline 13}{c +}{hline 56}
{space 7}trend {c |}{res}      2289    1992.905    6.557213       1981       2003
{txt}lagwopolgl~e {c |}{res}      2208    1.595807     .140961   1.336538    1.84375
{txt}{space 3}gdpgrowth {c |}{res}      2285    3.277674    6.220417  -50.24807   106.2798
{txt}{space 1}currencynew {c |}{res}      2289    5.518572    1.283248   3.302124    8.12675
{txt}{space 4}exchrate {c |}{res}      2288      320.99    1362.205   4.03e-11      25000
{txt}{hline 13}{c +}{hline 56}
{space 5}coldwar {c |}{res}      2289    .6684142    .4708859          0          1
{txt}{space 2}usalliance {c |}{res}      2289    .2516383    .4340493          0          1
{txt}{space 5}colbrit {c |}{res}      2289    .3272171    .4692998          0          1
{txt}{space 6}colfra {c |}{res}      2289    .2228047    .4162192          0          1
{txt}{space 6}nafrme {c |}{res}      2289    .1319353    .3384944          0          1
{txt}{hline 13}{c +}{hline 56}
{space 6}eeurop {c |}{res}      2289    .1131498    .3168451          0          1
{txt}{space 4}lamerica {c |}{res}      2289    .2057667    .4043491          0          1
{txt}{space 4}ssafrica {c |}{res}      2289    .3800786    .4855119          0          1
{txt}{space 8}asia {c |}{res}      2289    .1690695    .3748952          0          1
{txt}
{com}. 
. cmp(wecon = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme  lagweconglobe trend lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res} -850.8261
{txt}Iteration 2:   log likelihood = {res}-826.22945
{txt}Iteration 3:   log likelihood = {res}-825.49629
{txt}Iteration 4:   log likelihood = {res}-825.49434

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}14{txt}){col 67}= {res}    910.13
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-825.49434{txt}{col 51}Pseudo R2{col 67}= {res}    0.3554

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0792021{col 27}{space 2} .0754541{col 38}{space 1}   -1.05{col 47}{space 3}0.294{col 55}{space 4}-.2270894{col 68}{space 3} .0686853
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0213197{col 27}{space 2} .0064325{col 38}{space 1}    3.31{col 47}{space 3}0.001{col 55}{space 4} .0087123{col 68}{space 3} .0339271
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0075054{col 27}{space 2} .0062918{col 38}{space 1}    1.19{col 47}{space 3}0.233{col 55}{space 4}-.0048263{col 68}{space 3} .0198371
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2}  .086061{col 27}{space 2} .0414464{col 38}{space 1}    2.08{col 47}{space 3}0.038{col 55}{space 4} .0048275{col 68}{space 3} .1672945
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.4053029{col 27}{space 2} .2095197{col 38}{space 1}   -1.93{col 47}{space 3}0.053{col 55}{space 4} -.815954{col 68}{space 3} .0053481
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2910368{col 27}{space 2} .0981001{col 38}{space 1}    2.97{col 47}{space 3}0.003{col 55}{space 4} .0987642{col 68}{space 3} .4833094
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0852425{col 27}{space 2} .0256578{col 38}{space 1}   -3.32{col 47}{space 3}0.001{col 55}{space 4}-.1355308{col 68}{space 3}-.0349542
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2140617{col 27}{space 2} .0934324{col 38}{space 1}   -2.29{col 47}{space 3}0.022{col 55}{space 4}-.3971859{col 68}{space 3}-.0309375
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} .0591452{col 27}{space 2} .1209291{col 38}{space 1}    0.49{col 47}{space 3}0.625{col 55}{space 4}-.1778716{col 68}{space 3} .2961619
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.088336{col 27}{space 2}  .512255{col 38}{space 1}   -4.08{col 47}{space 3}0.000{col 55}{space 4}-3.092337{col 68}{space 3}-1.084334
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0187667{col 27}{space 2} .0075491{col 38}{space 1}   -2.49{col 47}{space 3}0.013{col 55}{space 4}-.0335627{col 68}{space 3}-.0039707
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.448391{col 27}{space 2} .1356105{col 38}{space 1}   10.68{col 47}{space 3}0.000{col 55}{space 4}   1.1826{col 68}{space 3} 1.714183
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.331201{col 27}{space 2}  .160347{col 38}{space 1}   20.77{col 47}{space 3}0.000{col 55}{space 4} 3.016926{col 68}{space 3} 3.645475
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.814471{col 27}{space 2} .4332275{col 38}{space 1}   11.11{col 47}{space 3}0.000{col 55}{space 4} 3.965361{col 68}{space 3} 5.663582
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2}-40.73551{col 27}{space 2} 14.76944{col 55}{space 4}-69.68308{col 68}{space 3}-11.78794
{txt}        /cut2 {c |}{col 15}{res}{space 2}-37.46631{col 27}{space 2} 14.75814{col 55}{space 4}-66.39173{col 68}{space 3}-8.540893
{txt}        /cut3 {c |}{col 15}{res}{space 2}-34.75367{col 27}{space 2} 14.75698{col 55}{space 4}-63.67681{col 68}{space 3}-5.830522
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 5010.538.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}14{txt}){col 67}= {res}    710.52
{txt}Log pseudolikelihood = {res} -2104.884{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.7807704{col 27}{space 2}  .211669{col 38}{space 1}   -3.69{col 47}{space 3}0.000{col 55}{space 4}-1.195634{col 68}{space 3}-.3659068
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0228105{col 27}{space 2} .0078681{col 38}{space 1}    2.90{col 47}{space 3}0.004{col 55}{space 4} .0073894{col 68}{space 3} .0382317
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} -.000595{col 27}{space 2} .0063795{col 38}{space 1}   -0.09{col 47}{space 3}0.926{col 55}{space 4}-.0130985{col 68}{space 3} .0119086
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0409057{col 27}{space 2} .0423464{col 38}{space 1}    0.97{col 47}{space 3}0.334{col 55}{space 4}-.0420918{col 68}{space 3} .1239031
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.3540519{col 27}{space 2} .1829169{col 38}{space 1}   -1.94{col 47}{space 3}0.053{col 55}{space 4}-.7125625{col 68}{space 3} .0044586
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2441972{col 27}{space 2} .1050495{col 38}{space 1}    2.32{col 47}{space 3}0.020{col 55}{space 4}  .038304{col 68}{space 3} .4500904
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0882692{col 27}{space 2} .0272657{col 38}{space 1}   -3.24{col 47}{space 3}0.001{col 55}{space 4} -.141709{col 68}{space 3}-.0348294
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2891764{col 27}{space 2} .1040847{col 38}{space 1}   -2.78{col 47}{space 3}0.005{col 55}{space 4}-.4931786{col 68}{space 3}-.0851742
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.0404367{col 27}{space 2} .2132469{col 38}{space 1}   -0.19{col 47}{space 3}0.850{col 55}{space 4} -.458393{col 68}{space 3} .3775196
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.084616{col 27}{space 2}   .55005{col 38}{space 1}   -3.79{col 47}{space 3}0.000{col 55}{space 4}-3.162694{col 68}{space 3}-1.006538
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0096455{col 27}{space 2} .0010567{col 38}{space 1}   -9.13{col 47}{space 3}0.000{col 55}{space 4}-.0117166{col 68}{space 3}-.0075744
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.353499{col 27}{space 2} .2750703{col 38}{space 1}    4.92{col 47}{space 3}0.000{col 55}{space 4} .8143709{col 68}{space 3} 1.892627
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.103063{col 27}{space 2} .3409299{col 38}{space 1}    9.10{col 47}{space 3}0.000{col 55}{space 4} 2.434853{col 68}{space 3} 3.771273
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.475897{col 27}{space 2} .5157087{col 38}{space 1}    8.68{col 47}{space 3}0.000{col 55}{space 4} 3.465126{col 68}{space 3} 5.486667
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1969535{col 27}{space 2} .0336296{col 38}{space 1}   -5.86{col 47}{space 3}0.000{col 55}{space 4}-.2628663{col 68}{space 3}-.1310407
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2}  .002313{col 27}{space 2} .0075986{col 38}{space 1}    0.30{col 47}{space 3}0.761{col 55}{space 4}-.0125799{col 68}{space 3} .0172059
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2547122{col 27}{space 2} .1146442{col 38}{space 1}   -2.22{col 47}{space 3}0.026{col 55}{space 4}-.4794106{col 68}{space 3}-.0300138
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000173{col 27}{space 2} .0000186{col 38}{space 1}    0.93{col 47}{space 3}0.352{col 55}{space 4}-.0000192{col 68}{space 3} .0000538
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0515009{col 27}{space 2} .1076944{col 38}{space 1}   -0.48{col 47}{space 3}0.632{col 55}{space 4}-.2625781{col 68}{space 3} .1595763
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0188463{col 27}{space 2} .0225083{col 38}{space 1}   -0.84{col 47}{space 3}0.402{col 55}{space 4}-.0629618{col 68}{space 3} .0252691
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .2407519{col 27}{space 2} .1244306{col 38}{space 1}    1.93{col 47}{space 3}0.053{col 55}{space 4}-.0031275{col 68}{space 3} .4846314
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8719947{col 27}{space 2} .2602257{col 38}{space 1}    3.35{col 47}{space 3}0.001{col 55}{space 4} .3619618{col 68}{space 3} 1.382028
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0869125{col 27}{space 2}  .183514{col 38}{space 1}    0.47{col 47}{space 3}0.636{col 55}{space 4}-.2727683{col 68}{space 3} .4465933
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4601734{col 27}{space 2} .2070636{col 38}{space 1}    2.22{col 47}{space 3}0.026{col 55}{space 4} .0543362{col 68}{space 3} .8660105
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9505074{col 27}{space 2} .2939043{col 38}{space 1}    3.23{col 47}{space 3}0.001{col 55}{space 4} .3744655{col 68}{space 3} 1.526549
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.1837824{col 27}{space 2}  .336743{col 38}{space 1}   -0.55{col 47}{space 3}0.585{col 55}{space 4}-.8437866{col 68}{space 3} .4762217
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6348849{col 27}{space 2}  .222543{col 38}{space 1}    2.85{col 47}{space 3}0.004{col 55}{space 4} .1987086{col 68}{space 3} 1.071061
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1518518{col 27}{space 2} .2518944{col 38}{space 1}    0.60{col 47}{space 3}0.547{col 55}{space 4} -.341852{col 68}{space 3} .6455557
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.030071{col 27}{space 2}  1.01139{col 38}{space 1}    1.02{col 47}{space 3}0.308{col 55}{space 4}-.9522163{col 68}{space 3} 3.012358
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .5123104{col 27}{space 2} .1500733{col 38}{space 1}    3.41{col 47}{space 3}0.001{col 55}{space 4} .2181721{col 68}{space 3} .8064487
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2}-23.17269{col 27}{space 2} 1.874536{col 38}{space 1}  -12.36{col 47}{space 3}0.000{col 55}{space 4}-26.84671{col 68}{space 3}-19.49867
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2}-20.08235{col 27}{space 2} 1.875668{col 38}{space 1}  -10.71{col 47}{space 3}0.000{col 55}{space 4}-23.75859{col 68}{space 3}-16.40611
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2}-17.51061{col 27}{space 2} 1.961529{col 38}{space 1}   -8.93{col 47}{space 3}0.000{col 55}{space 4}-21.35514{col 68}{space 3}-13.66609
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .4717434{col 27}{space 2} .1166757{col 55}{space 4} .2147751{col 68}{space 3} .6676265
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. sum wecon lagweconglobe if e(sample)

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 7}wecon {c |}{res}      2214    1.149051    .5505668          0          3
{txt}lagwecongl~e {c |}{res}      2208    1.167435     .070476   1.020408   1.301887
{txt}
{com}. 
. *Table AIII SINGLE STAGE MODELS FOR THE IMPACT OF W RIGHTS ON IMFDUMMY
. logit imfdummy wecon gdplog gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1443.1542}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1243.4911}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1236.7333}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1236.7224}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1236.7224}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2170
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}    295.96
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1236.7224{txt}{col 51}Pseudo R2{col 67}= {res}    0.1430

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    imfdummy{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}wecon {c |}{col 14}{res}{space 2} .0732569{col 26}{space 2} .0960155{col 37}{space 1}    0.76{col 46}{space 3}0.445{col 54}{space 4}-.1149299{col 67}{space 3} .2614438
{txt}{space 6}gdplog {c |}{col 14}{res}{space 2}-.8198134{col 26}{space 2} .0676098{col 37}{space 1}  -12.13{col 46}{space 3}0.000{col 54}{space 4}-.9523262{col 67}{space 3}-.6873006
{txt}{space 3}gdpgrowth {c |}{col 14}{res}{space 2} .0058006{col 26}{space 2} .0122528{col 37}{space 1}    0.47{col 46}{space 3}0.636{col 54}{space 4}-.0182145{col 67}{space 3} .0298156
{txt}{space 1}currencynew {c |}{col 14}{res}{space 2}-.3225405{col 26}{space 2} .1080807{col 37}{space 1}   -2.98{col 46}{space 3}0.003{col 54}{space 4}-.5343748{col 67}{space 3}-.1107063
{txt}{space 4}exchrate {c |}{col 14}{res}{space 2}  .000024{col 26}{space 2} .0000326{col 37}{space 1}    0.73{col 46}{space 3}0.463{col 54}{space 4}  -.00004{col 67}{space 3}  .000088
{txt}{space 4}tradelog {c |}{col 14}{res}{space 2} .1696929{col 26}{space 2} .1005106{col 37}{space 1}    1.69{col 46}{space 3}0.091{col 54}{space 4}-.0273042{col 67}{space 3} .3666901
{txt}{space 5}polity2 {c |}{col 14}{res}{space 2}-.0027978{col 26}{space 2} .0203547{col 37}{space 1}   -0.14{col 46}{space 3}0.891{col 54}{space 4}-.0426923{col 67}{space 3} .0370966
{txt}{space 5}coldwar {c |}{col 14}{res}{space 2} .2272663{col 26}{space 2} .1160828{col 37}{space 1}    1.96{col 46}{space 3}0.050{col 54}{space 4}-.0002518{col 67}{space 3} .4547844
{txt}{space 2}usalliance {c |}{col 14}{res}{space 2} 1.234027{col 26}{space 2} .2835811{col 37}{space 1}    4.35{col 46}{space 3}0.000{col 54}{space 4} .6782186{col 67}{space 3} 1.789836
{txt}{space 5}colbrit {c |}{col 14}{res}{space 2} .0862534{col 26}{space 2} .1445975{col 37}{space 1}    0.60{col 46}{space 3}0.551{col 54}{space 4}-.1971525{col 67}{space 3} .3696593
{txt}{space 6}colfra {c |}{col 14}{res}{space 2} .8092929{col 26}{space 2}  .163451{col 37}{space 1}    4.95{col 46}{space 3}0.000{col 54}{space 4} .4889348{col 67}{space 3} 1.129651
{txt}{space 6}eeurop {c |}{col 14}{res}{space 2} 1.231903{col 26}{space 2} .2684787{col 37}{space 1}    4.59{col 46}{space 3}0.000{col 54}{space 4} .7056945{col 67}{space 3} 1.758112
{txt}{space 4}lamerica {c |}{col 14}{res}{space 2}-.1966071{col 26}{space 2} .3417049{col 37}{space 1}   -0.58{col 46}{space 3}0.565{col 54}{space 4}-.8663363{col 67}{space 3} .4731222
{txt}{space 4}ssafrica {c |}{col 14}{res}{space 2} .5245254{col 26}{space 2} .2173636{col 37}{space 1}    2.41{col 46}{space 3}0.016{col 54}{space 4} .0985006{col 67}{space 3} .9505503
{txt}{space 8}asia {c |}{col 14}{res}{space 2} -.241236{col 26}{space 2} .2524155{col 37}{space 1}   -0.96{col 46}{space 3}0.339{col 54}{space 4}-.7359613{col 67}{space 3} .2534892
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 5.312455{col 26}{space 2} 1.119839{col 37}{space 1}    4.74{col 46}{space 3}0.000{col 54}{space 4}  3.11761{col 67}{space 3} 7.507299
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit imfdummy wopol gdplog gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1463.3094}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1262.5767}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1255.3666}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1255.3483}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1255.3483}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2206
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}    299.44
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1255.3483{txt}{col 51}Pseudo R2{col 67}= {res}    0.1421

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    imfdummy{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}wopol {c |}{col 14}{res}{space 2} .0324423{col 26}{space 2} .0964688{col 37}{space 1}    0.34{col 46}{space 3}0.737{col 54}{space 4}-.1566331{col 67}{space 3} .2215177
{txt}{space 6}gdplog {c |}{col 14}{res}{space 2}-.8140443{col 26}{space 2} .0661712{col 37}{space 1}  -12.30{col 46}{space 3}0.000{col 54}{space 4}-.9437375{col 67}{space 3}-.6843512
{txt}{space 3}gdpgrowth {c |}{col 14}{res}{space 2}   .00516{col 26}{space 2} .0118887{col 37}{space 1}    0.43{col 46}{space 3}0.664{col 54}{space 4}-.0181415{col 67}{space 3} .0284615
{txt}{space 1}currencynew {c |}{col 14}{res}{space 2}-.3254781{col 26}{space 2} .1058214{col 37}{space 1}   -3.08{col 46}{space 3}0.002{col 54}{space 4}-.5328842{col 67}{space 3} -.118072
{txt}{space 4}exchrate {c |}{col 14}{res}{space 2} .0000256{col 26}{space 2} .0000321{col 37}{space 1}    0.80{col 46}{space 3}0.425{col 54}{space 4}-.0000373{col 67}{space 3} .0000886
{txt}{space 4}tradelog {c |}{col 14}{res}{space 2} .1601122{col 26}{space 2} .0997397{col 37}{space 1}    1.61{col 46}{space 3}0.108{col 54}{space 4} -.035374{col 67}{space 3} .3555984
{txt}{space 5}polity2 {c |}{col 14}{res}{space 2}-.0011916{col 26}{space 2} .0201625{col 37}{space 1}   -0.06{col 46}{space 3}0.953{col 54}{space 4}-.0407094{col 67}{space 3} .0383261
{txt}{space 5}coldwar {c |}{col 14}{res}{space 2} .2101968{col 26}{space 2} .1148968{col 37}{space 1}    1.83{col 46}{space 3}0.067{col 54}{space 4}-.0149967{col 67}{space 3} .4353903
{txt}{space 2}usalliance {c |}{col 14}{res}{space 2} 1.254617{col 26}{space 2} .2825356{col 37}{space 1}    4.44{col 46}{space 3}0.000{col 54}{space 4}  .700857{col 67}{space 3} 1.808376
{txt}{space 5}colbrit {c |}{col 14}{res}{space 2} .1091295{col 26}{space 2} .1433589{col 37}{space 1}    0.76{col 46}{space 3}0.447{col 54}{space 4}-.1718487{col 67}{space 3} .3901078
{txt}{space 6}colfra {c |}{col 14}{res}{space 2} .8601792{col 26}{space 2} .1605971{col 37}{space 1}    5.36{col 46}{space 3}0.000{col 54}{space 4} .5454146{col 67}{space 3} 1.174944
{txt}{space 6}eeurop {c |}{col 14}{res}{space 2} 1.242711{col 26}{space 2} .2673954{col 37}{space 1}    4.65{col 46}{space 3}0.000{col 54}{space 4} .7186256{col 67}{space 3} 1.766796
{txt}{space 4}lamerica {c |}{col 14}{res}{space 2}-.2393259{col 26}{space 2} .3405438{col 37}{space 1}   -0.70{col 46}{space 3}0.482{col 54}{space 4}-.9067795{col 67}{space 3} .4281277
{txt}{space 4}ssafrica {c |}{col 14}{res}{space 2} .4903775{col 26}{space 2} .2159441{col 37}{space 1}    2.27{col 46}{space 3}0.023{col 54}{space 4} .0671349{col 67}{space 3} .9136201
{txt}{space 8}asia {c |}{col 14}{res}{space 2}-.2459772{col 26}{space 2} .2489767{col 37}{space 1}   -0.99{col 46}{space 3}0.323{col 54}{space 4}-.7339627{col 67}{space 3} .2420083
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   5.3376{col 26}{space 2} 1.111235{col 37}{space 1}    4.80{col 46}{space 3}0.000{col 54}{space 4}  3.15962{col 67}{space 3}  7.51558
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit imfdummy wecon wopol gdplog gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1435.4433}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1238.9993}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1231.9719}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1231.9534}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1231.9534}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2161
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    294.24
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1231.9534{txt}{col 51}Pseudo R2{col 67}= {res}    0.1418

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}    imfdummy{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}wecon {c |}{col 14}{res}{space 2} .0756687{col 26}{space 2} .0979941{col 37}{space 1}    0.77{col 46}{space 3}0.440{col 54}{space 4}-.1163963{col 67}{space 3} .2677336
{txt}{space 7}wopol {c |}{col 14}{res}{space 2} .0089012{col 26}{space 2} .0988721{col 37}{space 1}    0.09{col 46}{space 3}0.928{col 54}{space 4}-.1848846{col 67}{space 3} .2026869
{txt}{space 6}gdplog {c |}{col 14}{res}{space 2}-.8122949{col 26}{space 2} .0675124{col 37}{space 1}  -12.03{col 46}{space 3}0.000{col 54}{space 4}-.9446167{col 67}{space 3}-.6799731
{txt}{space 3}gdpgrowth {c |}{col 14}{res}{space 2} .0057894{col 26}{space 2}  .012294{col 37}{space 1}    0.47{col 46}{space 3}0.638{col 54}{space 4}-.0183063{col 67}{space 3} .0298852
{txt}{space 1}currencynew {c |}{col 14}{res}{space 2}-.3137873{col 26}{space 2} .1080527{col 37}{space 1}   -2.90{col 46}{space 3}0.004{col 54}{space 4}-.5255667{col 67}{space 3}-.1020078
{txt}{space 4}exchrate {c |}{col 14}{res}{space 2} .0000245{col 26}{space 2} .0000327{col 37}{space 1}    0.75{col 46}{space 3}0.453{col 54}{space 4}-.0000395{col 67}{space 3} .0000885
{txt}{space 4}tradelog {c |}{col 14}{res}{space 2} .1693155{col 26}{space 2} .1006641{col 37}{space 1}    1.68{col 46}{space 3}0.093{col 54}{space 4}-.0279825{col 67}{space 3} .3666136
{txt}{space 5}polity2 {c |}{col 14}{res}{space 2}-.0008715{col 26}{space 2} .0204449{col 37}{space 1}   -0.04{col 46}{space 3}0.966{col 54}{space 4}-.0409429{col 67}{space 3} .0391998
{txt}{space 5}coldwar {c |}{col 14}{res}{space 2} .2108373{col 26}{space 2} .1171377{col 37}{space 1}    1.80{col 46}{space 3}0.072{col 54}{space 4}-.0187484{col 67}{space 3}  .440423
{txt}{space 2}usalliance {c |}{col 14}{res}{space 2} 1.224764{col 26}{space 2} .2828297{col 37}{space 1}    4.33{col 46}{space 3}0.000{col 54}{space 4} .6704277{col 67}{space 3}   1.7791
{txt}{space 5}colbrit {c |}{col 14}{res}{space 2} .0754698{col 26}{space 2} .1455151{col 37}{space 1}    0.52{col 46}{space 3}0.604{col 54}{space 4}-.2097344{col 67}{space 3} .3606741
{txt}{space 6}colfra {c |}{col 14}{res}{space 2} .8175657{col 26}{space 2} .1631387{col 37}{space 1}    5.01{col 46}{space 3}0.000{col 54}{space 4} .4978198{col 67}{space 3} 1.137312
{txt}{space 6}eeurop {c |}{col 14}{res}{space 2} 1.227095{col 26}{space 2} .2706518{col 37}{space 1}    4.53{col 46}{space 3}0.000{col 54}{space 4} .6966273{col 67}{space 3} 1.757563
{txt}{space 4}lamerica {c |}{col 14}{res}{space 2}-.2078918{col 26}{space 2}  .343396{col 37}{space 1}   -0.61{col 46}{space 3}0.545{col 54}{space 4}-.8809356{col 67}{space 3} .4651521
{txt}{space 4}ssafrica {c |}{col 14}{res}{space 2} .5176644{col 26}{space 2} .2190415{col 37}{space 1}    2.36{col 46}{space 3}0.018{col 54}{space 4} .0883509{col 67}{space 3} .9469779
{txt}{space 8}asia {c |}{col 14}{res}{space 2}-.2365166{col 26}{space 2} .2526888{col 37}{space 1}   -0.94{col 46}{space 3}0.349{col 54}{space 4}-.7317776{col 67}{space 3} .2587444
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 5.187254{col 26}{space 2} 1.123404{col 37}{space 1}    4.62{col 46}{space 3}0.000{col 54}{space 4} 2.985422{col 67}{space 3} 7.389086
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. ***** ONLINE APPENDIX TABLES ******
. *ROBUSTNESS CHECK : RELIGION DUMMIES ADDED
. cmp(wecon = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagweconglobe trend budhismdom catholicdom hinduismdom islamdom protestantdom   lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res}-847.10549
{txt}Iteration 2:   log likelihood = {res}-821.37078
{txt}Iteration 3:   log likelihood = {res}-820.53759
{txt}Iteration 4:   log likelihood = {res}-820.53521

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}19{txt}){col 67}= {res}    920.05
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-820.53521{txt}{col 51}Pseudo R2{col 67}= {res}    0.3592

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0589001{col 27}{space 2} .0762486{col 38}{space 1}   -0.77{col 47}{space 3}0.440{col 55}{space 4}-.2083446{col 68}{space 3} .0905443
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0158248{col 27}{space 2} .0067846{col 38}{space 1}    2.33{col 47}{space 3}0.020{col 55}{space 4} .0025272{col 68}{space 3} .0291223
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0062174{col 27}{space 2} .0063556{col 38}{space 1}    0.98{col 47}{space 3}0.328{col 55}{space 4}-.0062395{col 68}{space 3} .0186742
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0829074{col 27}{space 2} .0423129{col 38}{space 1}    1.96{col 47}{space 3}0.050{col 55}{space 4}-.0000244{col 68}{space 3} .1658392
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.4168244{col 27}{space 2} .2109079{col 38}{space 1}   -1.98{col 47}{space 3}0.048{col 55}{space 4}-.8301964{col 68}{space 3}-.0034524
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2247656{col 27}{space 2} .1021576{col 38}{space 1}    2.20{col 47}{space 3}0.028{col 55}{space 4} .0245405{col 68}{space 3} .4249907
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0814457{col 27}{space 2} .0274191{col 38}{space 1}   -2.97{col 47}{space 3}0.003{col 55}{space 4}-.1351861{col 68}{space 3}-.0277053
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2255952{col 27}{space 2} .0954165{col 38}{space 1}   -2.36{col 47}{space 3}0.018{col 55}{space 4}-.4126081{col 68}{space 3}-.0385822
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} .2529147{col 27}{space 2} .1562151{col 38}{space 1}    1.62{col 47}{space 3}0.105{col 55}{space 4}-.0532613{col 68}{space 3} .5590907
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.083507{col 27}{space 2} .5142439{col 38}{space 1}   -4.05{col 47}{space 3}0.000{col 55}{space 4}-3.091407{col 68}{space 3}-1.075608
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0140515{col 27}{space 2} .0078141{col 38}{space 1}   -1.80{col 47}{space 3}0.072{col 55}{space 4}-.0293668{col 68}{space 3} .0012638
{txt}{space 3}budhismdom {c |}{col 15}{res}{space 2} .3021967{col 27}{space 2} .2196906{col 38}{space 1}    1.38{col 47}{space 3}0.169{col 55}{space 4} -.128389{col 68}{space 3} .7327824
{txt}{space 2}catholicdom {c |}{col 15}{res}{space 2} .1812071{col 27}{space 2} .0928076{col 38}{space 1}    1.95{col 47}{space 3}0.051{col 55}{space 4}-.0006925{col 68}{space 3} .3631066
{txt}{space 2}hinduismdom {c |}{col 15}{res}{space 2}-.0148487{col 27}{space 2} .2664764{col 38}{space 1}   -0.06{col 47}{space 3}0.956{col 55}{space 4}-.5371328{col 68}{space 3} .5074354
{txt}{space 5}islamdom {c |}{col 15}{res}{space 2}-.1926917{col 27}{space 2} .1270277{col 38}{space 1}   -1.52{col 47}{space 3}0.129{col 55}{space 4}-.4416615{col 68}{space 3}  .056278
{txt}protestantdom {c |}{col 15}{res}{space 2} .0632442{col 27}{space 2} .3819158{col 38}{space 1}    0.17{col 47}{space 3}0.868{col 55}{space 4}-.6852969{col 68}{space 3} .8117854
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.408966{col 27}{space 2}  .137818{col 38}{space 1}   10.22{col 47}{space 3}0.000{col 55}{space 4} 1.138847{col 68}{space 3} 1.679084
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.282243{col 27}{space 2}  .162269{col 38}{space 1}   20.23{col 47}{space 3}0.000{col 55}{space 4} 2.964202{col 68}{space 3} 3.600285
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.772957{col 27}{space 2}  .432949{col 38}{space 1}   11.02{col 47}{space 3}0.000{col 55}{space 4} 3.924393{col 68}{space 3} 5.621521
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2}-31.42162{col 27}{space 2} 15.27945{col 55}{space 4}-61.36879{col 68}{space 3}-1.474444
{txt}        /cut2 {c |}{col 15}{res}{space 2}-28.12292{col 27}{space 2} 15.27031{col 55}{space 4}-58.05217{col 68}{space 3} 1.806343
{txt}        /cut3 {c |}{col 15}{res}{space 2}-25.40813{col 27}{space 2} 15.26991{col 55}{space 4} -55.3366{col 68}{space 3} 4.520346
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 5605.7709.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}19{txt}){col 67}= {res}    666.68
{txt}Log pseudolikelihood = {res}-2101.5831{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2} -.722322{col 27}{space 2} .2231243{col 38}{space 1}   -3.24{col 47}{space 3}0.001{col 55}{space 4}-1.159638{col 68}{space 3}-.2850063
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0186023{col 27}{space 2} .0085407{col 38}{space 1}    2.18{col 47}{space 3}0.029{col 55}{space 4} .0018629{col 68}{space 3} .0353417
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0011866{col 27}{space 2} .0065963{col 38}{space 1}   -0.18{col 47}{space 3}0.857{col 55}{space 4}-.0141151{col 68}{space 3}  .011742
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0418802{col 27}{space 2} .0413293{col 38}{space 1}    1.01{col 47}{space 3}0.311{col 55}{space 4}-.0391238{col 68}{space 3} .1228841
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.3702837{col 27}{space 2} .1873079{col 38}{space 1}   -1.98{col 47}{space 3}0.048{col 55}{space 4}-.7374004{col 68}{space 3} -.003167
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .1941496{col 27}{space 2} .1114368{col 38}{space 1}    1.74{col 47}{space 3}0.081{col 55}{space 4}-.0242624{col 68}{space 3} .4125616
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0849697{col 27}{space 2} .0289507{col 38}{space 1}   -2.93{col 47}{space 3}0.003{col 55}{space 4}-.1417121{col 68}{space 3}-.0282273
{txt}civilconflict {c |}{col 15}{res}{space 2} -.291525{col 27}{space 2} .1110543{col 38}{space 1}   -2.63{col 47}{space 3}0.009{col 55}{space 4}-.5091875{col 68}{space 3}-.0738626
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} .1117653{col 27}{space 2}  .292926{col 38}{space 1}    0.38{col 47}{space 3}0.703{col 55}{space 4}-.4623591{col 68}{space 3} .6858897
{txt}lagweconglobe {c |}{col 15}{res}{space 2} -2.08553{col 27}{space 2} .5537189{col 38}{space 1}   -3.77{col 47}{space 3}0.000{col 55}{space 4}-3.170799{col 68}{space 3}-1.000261
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0065993{col 27}{space 2} .0010156{col 38}{space 1}   -6.50{col 47}{space 3}0.000{col 55}{space 4}-.0085898{col 68}{space 3}-.0046088
{txt}{space 3}budhismdom {c |}{col 15}{res}{space 2} .2208797{col 27}{space 2} .2351554{col 38}{space 1}    0.94{col 47}{space 3}0.348{col 55}{space 4}-.2400164{col 68}{space 3} .6817759
{txt}{space 2}catholicdom {c |}{col 15}{res}{space 2} .1478987{col 27}{space 2}  .109335{col 38}{space 1}    1.35{col 47}{space 3}0.176{col 55}{space 4}-.0663939{col 68}{space 3} .3621913
{txt}{space 2}hinduismdom {c |}{col 15}{res}{space 2}-.0541786{col 27}{space 2} .1882221{col 38}{space 1}   -0.29{col 47}{space 3}0.773{col 55}{space 4}-.4230872{col 68}{space 3} .3147299
{txt}{space 5}islamdom {c |}{col 15}{res}{space 2}-.1439625{col 27}{space 2}  .176749{col 38}{space 1}   -0.81{col 47}{space 3}0.415{col 55}{space 4}-.4903841{col 68}{space 3} .2024591
{txt}protestantdom {c |}{col 15}{res}{space 2}-.0226062{col 27}{space 2} .5216178{col 38}{space 1}   -0.04{col 47}{space 3}0.965{col 55}{space 4}-1.044958{col 68}{space 3} .9997459
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.338225{col 27}{space 2} .2819091{col 38}{space 1}    4.75{col 47}{space 3}0.000{col 55}{space 4} .7856938{col 68}{space 3} 1.890757
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.094368{col 27}{space 2} .3458246{col 38}{space 1}    8.95{col 47}{space 3}0.000{col 55}{space 4} 2.416564{col 68}{space 3} 3.772171
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.484218{col 27}{space 2} .5366854{col 38}{space 1}    8.36{col 47}{space 3}0.000{col 55}{space 4} 3.432334{col 68}{space 3} 5.536102
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1967951{col 27}{space 2} .0336429{col 38}{space 1}   -5.85{col 47}{space 3}0.000{col 55}{space 4}-.2627339{col 68}{space 3}-.1308562
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0022155{col 27}{space 2} .0076076{col 38}{space 1}    0.29{col 47}{space 3}0.771{col 55}{space 4}-.0126952{col 68}{space 3} .0171262
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2543587{col 27}{space 2} .1152655{col 38}{space 1}   -2.21{col 47}{space 3}0.027{col 55}{space 4} -.480275{col 68}{space 3}-.0284425
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000168{col 27}{space 2} .0000188{col 38}{space 1}    0.89{col 47}{space 3}0.373{col 55}{space 4}-.0000201{col 68}{space 3} .0000537
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0506508{col 27}{space 2} .1072204{col 38}{space 1}   -0.47{col 47}{space 3}0.637{col 55}{space 4} -.260799{col 68}{space 3} .1594973
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0192112{col 27}{space 2} .0226468{col 38}{space 1}   -0.85{col 47}{space 3}0.396{col 55}{space 4} -.063598{col 68}{space 3} .0251756
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2}  .239031{col 27}{space 2} .1257365{col 38}{space 1}    1.90{col 47}{space 3}0.057{col 55}{space 4}-.0074079{col 68}{space 3} .4854699
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8673409{col 27}{space 2}  .261986{col 38}{space 1}    3.31{col 47}{space 3}0.001{col 55}{space 4} .3538578{col 68}{space 3} 1.380824
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0707827{col 27}{space 2} .1847237{col 38}{space 1}    0.38{col 47}{space 3}0.702{col 55}{space 4}-.2912692{col 68}{space 3} .4328346
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4511669{col 27}{space 2} .2087058{col 38}{space 1}    2.16{col 47}{space 3}0.031{col 55}{space 4} .0421109{col 68}{space 3} .8602228
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9437158{col 27}{space 2} .2952255{col 38}{space 1}    3.20{col 47}{space 3}0.001{col 55}{space 4} .3650845{col 68}{space 3} 1.522347
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.1705888{col 27}{space 2} .3372731{col 38}{space 1}   -0.51{col 47}{space 3}0.613{col 55}{space 4} -.831632{col 68}{space 3} .4904544
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6313845{col 27}{space 2} .2231322{col 38}{space 1}    2.83{col 47}{space 3}0.005{col 55}{space 4} .1940534{col 68}{space 3} 1.068716
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1448983{col 27}{space 2} .2536045{col 38}{space 1}    0.57{col 47}{space 3}0.568{col 55}{space 4}-.3521574{col 68}{space 3} .6419541
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.039365{col 27}{space 2} 1.014735{col 38}{space 1}    1.02{col 47}{space 3}0.306{col 55}{space 4}-.9494787{col 68}{space 3} 3.028208
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .4759104{col 27}{space 2} .1546149{col 38}{space 1}    3.08{col 47}{space 3}0.002{col 55}{space 4} .1728707{col 68}{space 3} .7789501
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} -17.1258{col 27}{space 2}  1.75819{col 38}{space 1}   -9.74{col 47}{space 3}0.000{col 55}{space 4}-20.57178{col 68}{space 3}-13.67981
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2}-13.98734{col 27}{space 2} 1.759887{col 38}{space 1}   -7.95{col 47}{space 3}0.000{col 55}{space 4}-17.43666{col 68}{space 3}-10.53803
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2}-11.39577{col 27}{space 2} 1.830654{col 38}{space 1}   -6.22{col 47}{space 3}0.000{col 55}{space 4}-14.98379{col 68}{space 3}-7.807757
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .4429624{col 27}{space 2} .1242771{col 55}{space 4}  .171169{col 68}{space 3} .6521037
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wopol = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagwopolglobe trend budhismdom catholicdom hinduismdom islamdom protestantdom   lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res}-653.04435
{txt}Iteration 2:   log likelihood = {res}-593.94639
{txt}Iteration 3:   log likelihood = {res}-590.03686
{txt}Iteration 4:   log likelihood = {res}-589.99869
{txt}Iteration 5:   log likelihood = {res}-589.99868

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}19{txt}){col 67}= {res}   1488.36
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-589.99868{txt}{col 51}Pseudo R2{col 67}= {res}    0.5578

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0349706{col 27}{space 2} .0893116{col 38}{space 1}   -0.39{col 47}{space 3}0.695{col 55}{space 4}-.2100181{col 68}{space 3} .1400769
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0062683{col 27}{space 2} .0076842{col 38}{space 1}    0.82{col 47}{space 3}0.415{col 55}{space 4}-.0087924{col 68}{space 3} .0213291
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0412496{col 27}{space 2} .0094324{col 38}{space 1}   -4.37{col 47}{space 3}0.000{col 55}{space 4}-.0597367{col 68}{space 3}-.0227624
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0363527{col 27}{space 2} .0500473{col 38}{space 1}    0.73{col 47}{space 3}0.468{col 55}{space 4}-.0617382{col 68}{space 3} .1344435
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.1327451{col 27}{space 2} .2656432{col 38}{space 1}   -0.50{col 47}{space 3}0.617{col 55}{space 4}-.6533962{col 68}{space 3}  .387906
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2000047{col 27}{space 2} .1095522{col 38}{space 1}    1.83{col 47}{space 3}0.068{col 55}{space 4}-.0147137{col 68}{space 3} .4147231
{txt}lntotalfempop {c |}{col 15}{res}{space 2}    .0183{col 27}{space 2} .0327911{col 38}{space 1}    0.56{col 47}{space 3}0.577{col 55}{space 4}-.0459693{col 68}{space 3} .0825694
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1246934{col 27}{space 2} .1056675{col 38}{space 1}   -1.18{col 47}{space 3}0.238{col 55}{space 4}-.3317979{col 68}{space 3}  .082411
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.1164476{col 27}{space 2}  .165109{col 38}{space 1}   -0.71{col 47}{space 3}0.481{col 55}{space 4}-.4400553{col 68}{space 3} .2071601
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.311768{col 27}{space 2} .8590941{col 38}{space 1}   -1.53{col 47}{space 3}0.127{col 55}{space 4}-2.995561{col 68}{space 3} .3720259
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0551793{col 27}{space 2} .0200153{col 38}{space 1}    2.76{col 47}{space 3}0.006{col 55}{space 4} .0159501{col 68}{space 3} .0944085
{txt}{space 3}budhismdom {c |}{col 15}{res}{space 2}-.1088432{col 27}{space 2} .2635163{col 38}{space 1}   -0.41{col 47}{space 3}0.680{col 55}{space 4}-.6253257{col 68}{space 3} .4076393
{txt}{space 2}catholicdom {c |}{col 15}{res}{space 2} .3049346{col 27}{space 2} .1178338{col 38}{space 1}    2.59{col 47}{space 3}0.010{col 55}{space 4} .0739846{col 68}{space 3} .5358847
{txt}{space 2}hinduismdom {c |}{col 15}{res}{space 2}-.0899505{col 27}{space 2} .2701824{col 38}{space 1}   -0.33{col 47}{space 3}0.739{col 55}{space 4}-.6194982{col 68}{space 3} .4395973
{txt}{space 5}islamdom {c |}{col 15}{res}{space 2}-.2957019{col 27}{space 2} .1417095{col 38}{space 1}   -2.09{col 47}{space 3}0.037{col 55}{space 4}-.5734474{col 68}{space 3}-.0179564
{txt}protestantdom {c |}{col 15}{res}{space 2}-.6214641{col 27}{space 2}  .335013{col 38}{space 1}   -1.86{col 47}{space 3}0.064{col 55}{space 4}-1.278077{col 68}{space 3} .0351493
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.169182{col 27}{space 2} .1751647{col 38}{space 1}    6.67{col 47}{space 3}0.000{col 55}{space 4} .8258651{col 68}{space 3} 1.512498
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.484315{col 27}{space 2} .1876848{col 38}{space 1}   18.56{col 47}{space 3}0.000{col 55}{space 4}  3.11646{col 68}{space 3} 3.852171
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.745666{col 27}{space 2} .4881606{col 38}{space 1}   13.82{col 47}{space 3}0.000{col 55}{space 4} 5.788889{col 68}{space 3} 7.702443
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 107.8041{col 27}{space 2} 38.60665{col 55}{space 4} 32.13642{col 68}{space 3} 183.4717
{txt}        /cut2 {c |}{col 15}{res}{space 2} 110.2609{col 27}{space 2} 38.61403{col 55}{space 4} 34.57878{col 68}{space 3}  185.943
{txt}        /cut3 {c |}{col 15}{res}{space 2} 114.5503{col 27}{space 2} 38.63021{col 55}{space 4}  38.8365{col 68}{space 3} 190.2641
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3984.3952.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}19{txt}){col 67}= {res}  23994.98
{txt}Log pseudolikelihood = {res}-1876.2152{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.2729582{col 27}{space 2} .1926322{col 38}{space 1}   -1.42{col 47}{space 3}0.156{col 55}{space 4}-.6505104{col 68}{space 3} .1045941
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0071975{col 27}{space 2} .0075598{col 38}{space 1}    0.95{col 47}{space 3}0.341{col 55}{space 4}-.0076194{col 68}{space 3} .0220144
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0446103{col 27}{space 2} .0102163{col 38}{space 1}   -4.37{col 47}{space 3}0.000{col 55}{space 4}-.0646339{col 68}{space 3}-.0245866
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2}  .021594{col 27}{space 2} .0480969{col 38}{space 1}    0.45{col 47}{space 3}0.653{col 55}{space 4}-.0726742{col 68}{space 3} .1158622
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.1211054{col 27}{space 2}  .293151{col 38}{space 1}   -0.41{col 47}{space 3}0.680{col 55}{space 4}-.6956708{col 68}{space 3} .4534601
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .1936667{col 27}{space 2} .1070271{col 38}{space 1}    1.81{col 47}{space 3}0.070{col 55}{space 4}-.0161025{col 68}{space 3} .4034359
{txt}lntotalfempop {c |}{col 15}{res}{space 2} .0142177{col 27}{space 2} .0376819{col 38}{space 1}    0.38{col 47}{space 3}0.706{col 55}{space 4}-.0596374{col 68}{space 3} .0880729
{txt}civilconflict {c |}{col 15}{res}{space 2} -.152383{col 27}{space 2} .1083041{col 38}{space 1}   -1.41{col 47}{space 3}0.159{col 55}{space 4}-.3646552{col 68}{space 3} .0598892
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.1759816{col 27}{space 2} .1879612{col 38}{space 1}   -0.94{col 47}{space 3}0.349{col 55}{space 4}-.5443787{col 68}{space 3} .1924156
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.393506{col 27}{space 2} .4166772{col 38}{space 1}   -3.34{col 47}{space 3}0.001{col 55}{space 4}-2.210179{col 68}{space 3} -.576834
{txt}{space 8}trend {c |}{col 15}{res}{space 2}  .059462{col 27}{space 2} .0006636{col 38}{space 1}   89.61{col 47}{space 3}0.000{col 55}{space 4} .0581614{col 68}{space 3} .0607626
{txt}{space 3}budhismdom {c |}{col 15}{res}{space 2}  -.13122{col 27}{space 2} .2627505{col 38}{space 1}   -0.50{col 47}{space 3}0.617{col 55}{space 4}-.6462015{col 68}{space 3} .3837614
{txt}{space 2}catholicdom {c |}{col 15}{res}{space 2} .2965115{col 27}{space 2} .1340444{col 38}{space 1}    2.21{col 47}{space 3}0.027{col 55}{space 4} .0337894{col 68}{space 3} .5592336
{txt}{space 2}hinduismdom {c |}{col 15}{res}{space 2}-.1030872{col 27}{space 2} .2308605{col 38}{space 1}   -0.45{col 47}{space 3}0.655{col 55}{space 4}-.5555655{col 68}{space 3}  .349391
{txt}{space 5}islamdom {c |}{col 15}{res}{space 2}-.2712658{col 27}{space 2} .1532242{col 38}{space 1}   -1.77{col 47}{space 3}0.077{col 55}{space 4}-.5715797{col 68}{space 3} .0290481
{txt}protestantdom {c |}{col 15}{res}{space 2}-.6556026{col 27}{space 2} .1725039{col 38}{space 1}   -3.80{col 47}{space 3}0.000{col 55}{space 4}-.9937039{col 68}{space 3}-.3175012
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.160622{col 27}{space 2} .3341008{col 38}{space 1}    3.47{col 47}{space 3}0.001{col 55}{space 4} .5057965{col 68}{space 3} 1.815447
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.458539{col 27}{space 2} .3864272{col 38}{space 1}    8.95{col 47}{space 3}0.000{col 55}{space 4} 2.701156{col 68}{space 3} 4.215923
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.686865{col 27}{space 2}  .569089{col 38}{space 1}   11.75{col 47}{space 3}0.000{col 55}{space 4} 5.571471{col 68}{space 3} 7.802259
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1962847{col 27}{space 2} .0334934{col 38}{space 1}   -5.86{col 47}{space 3}0.000{col 55}{space 4}-.2619307{col 68}{space 3}-.1306388
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0017387{col 27}{space 2} .0076703{col 38}{space 1}    0.23{col 47}{space 3}0.821{col 55}{space 4}-.0132947{col 68}{space 3} .0167722
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2} -.247292{col 27}{space 2} .1157642{col 38}{space 1}   -2.14{col 47}{space 3}0.033{col 55}{space 4}-.4741857{col 68}{space 3}-.0203983
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000143{col 27}{space 2} .0000199{col 38}{space 1}    0.72{col 47}{space 3}0.474{col 55}{space 4}-.0000248{col 68}{space 3} .0000533
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0434333{col 27}{space 2} .1065618{col 38}{space 1}   -0.41{col 47}{space 3}0.684{col 55}{space 4}-.2522907{col 68}{space 3} .1654241
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0160928{col 27}{space 2} .0224941{col 38}{space 1}   -0.72{col 47}{space 3}0.474{col 55}{space 4}-.0601804{col 68}{space 3} .0279948
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .1952047{col 27}{space 2} .1215071{col 38}{space 1}    1.61{col 47}{space 3}0.108{col 55}{space 4}-.0429448{col 68}{space 3} .4333541
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8426552{col 27}{space 2} .2734774{col 38}{space 1}    3.08{col 47}{space 3}0.002{col 55}{space 4} .3066493{col 68}{space 3} 1.378661
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0358006{col 27}{space 2} .1879548{col 38}{space 1}    0.19{col 47}{space 3}0.849{col 55}{space 4}-.3325841{col 68}{space 3} .4041853
{txt}{space 7}colfra {c |}{col 15}{res}{space 2}  .461217{col 27}{space 2} .2122814{col 38}{space 1}    2.17{col 47}{space 3}0.030{col 55}{space 4} .0451531{col 68}{space 3} .8772809
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9323905{col 27}{space 2} .3021184{col 38}{space 1}    3.09{col 47}{space 3}0.002{col 55}{space 4} .3402494{col 68}{space 3} 1.524532
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.2053673{col 27}{space 2} .3490134{col 38}{space 1}   -0.59{col 47}{space 3}0.556{col 55}{space 4} -.889421{col 68}{space 3} .4786863
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6105812{col 27}{space 2} .2233586{col 38}{space 1}    2.73{col 47}{space 3}0.006{col 55}{space 4} .1728065{col 68}{space 3} 1.048356
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1131368{col 27}{space 2} .2575845{col 38}{space 1}    0.44{col 47}{space 3}0.661{col 55}{space 4}-.3917196{col 68}{space 3} .6179932
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.002171{col 27}{space 2} 1.025528{col 38}{space 1}    0.98{col 47}{space 3}0.328{col 55}{space 4}-1.007827{col 68}{space 3} 3.012169
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1563587{col 27}{space 2}  .105708{col 38}{space 1}    1.48{col 47}{space 3}0.139{col 55}{space 4}-.0508252{col 68}{space 3} .3635427
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 115.9644{col 27}{space 2} .8983122{col 38}{space 1}  129.09{col 47}{space 3}0.000{col 55}{space 4} 114.2037{col 68}{space 3}  117.725
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 118.4055{col 27}{space 2} .9004446{col 38}{space 1}  131.50{col 47}{space 3}0.000{col 55}{space 4} 116.6406{col 68}{space 3} 120.1703
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2}  122.663{col 27}{space 2} .8988899{col 38}{space 1}  136.46{col 47}{space 3}0.000{col 55}{space 4} 120.9012{col 68}{space 3} 124.4248
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1550968{col 27}{space 2} .1031652{col 55}{space 4}-.0507815{col 68}{space 3} .3483307
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *ROBUSTNESS CHECK : Ethnic and Religious Fractionalization
. cmp(wecon = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagweconglobe trend ef relfrac lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res}-847.56521
{txt}Iteration 2:   log likelihood = {res}-821.97271
{txt}Iteration 3:   log likelihood = {res}-821.14814
{txt}Iteration 4:   log likelihood = {res}-821.14565

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}16{txt}){col 67}= {res}    918.83
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-821.14565{txt}{col 51}Pseudo R2{col 67}= {res}    0.3588

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0574278{col 27}{space 2} .0760364{col 38}{space 1}   -0.76{col 47}{space 3}0.450{col 55}{space 4}-.2064564{col 68}{space 3} .0916008
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0178292{col 27}{space 2} .0067343{col 38}{space 1}    2.65{col 47}{space 3}0.008{col 55}{space 4} .0046303{col 68}{space 3} .0310282
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0084947{col 27}{space 2}  .006353{col 38}{space 1}    1.34{col 47}{space 3}0.181{col 55}{space 4} -.003957{col 68}{space 3} .0209464
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0695585{col 27}{space 2} .0423634{col 38}{space 1}    1.64{col 47}{space 3}0.101{col 55}{space 4}-.0134723{col 68}{space 3} .1525894
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.4235371{col 27}{space 2} .2116213{col 38}{space 1}   -2.00{col 47}{space 3}0.045{col 55}{space 4}-.8383073{col 68}{space 3}-.0087669
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2310724{col 27}{space 2} .1018895{col 38}{space 1}    2.27{col 47}{space 3}0.023{col 55}{space 4} .0313727{col 68}{space 3}  .430772
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0940726{col 27}{space 2} .0267562{col 38}{space 1}   -3.52{col 47}{space 3}0.000{col 55}{space 4}-.1465138{col 68}{space 3}-.0416314
{txt}civilconflict {c |}{col 15}{res}{space 2}-.1936225{col 27}{space 2} .0939975{col 38}{space 1}   -2.06{col 47}{space 3}0.039{col 55}{space 4}-.3778541{col 68}{space 3}-.0093908
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.0336596{col 27}{space 2} .1383835{col 38}{space 1}   -0.24{col 47}{space 3}0.808{col 55}{space 4}-.3048863{col 68}{space 3} .2375671
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.089948{col 27}{space 2} .5137102{col 38}{space 1}   -4.07{col 47}{space 3}0.000{col 55}{space 4}-3.096802{col 68}{space 3}-1.083095
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0147277{col 27}{space 2} .0079409{col 38}{space 1}   -1.85{col 47}{space 3}0.064{col 55}{space 4}-.0302915{col 68}{space 3} .0008361
{txt}{space 11}ef {c |}{col 15}{res}{space 2}-.4551375{col 27}{space 2} .1592874{col 38}{space 1}   -2.86{col 47}{space 3}0.004{col 55}{space 4} -.767335{col 68}{space 3}  -.14294
{txt}{space 6}relfrac {c |}{col 15}{res}{space 2} .0322649{col 27}{space 2} .2103543{col 38}{space 1}    0.15{col 47}{space 3}0.878{col 55}{space 4} -.380022{col 68}{space 3} .4445517
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2}  1.43362{col 27}{space 2} .1360438{col 38}{space 1}   10.54{col 47}{space 3}0.000{col 55}{space 4} 1.166979{col 68}{space 3} 1.700261
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.323104{col 27}{space 2}  .160781{col 38}{space 1}   20.67{col 47}{space 3}0.000{col 55}{space 4} 3.007979{col 68}{space 3} 3.638229
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.771243{col 27}{space 2} .4342207{col 38}{space 1}   10.99{col 47}{space 3}0.000{col 55}{space 4} 3.920186{col 68}{space 3} 5.622299
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2}-33.25926{col 27}{space 2} 15.47031{col 55}{space 4}-63.58051{col 68}{space 3}-2.938016
{txt}        /cut2 {c |}{col 15}{res}{space 2}-29.96844{col 27}{space 2} 15.46168{col 55}{space 4}-60.27278{col 68}{space 3} .3359021
{txt}        /cut3 {c |}{col 15}{res}{space 2}-27.23895{col 27}{space 2} 15.46059{col 55}{space 4}-57.54116{col 68}{space 3} 3.063252
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 6225.5916.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    618.12
{txt}Log pseudolikelihood = {res}-2102.2757{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.7140478{col 27}{space 2} .2329401{col 38}{space 1}   -3.07{col 47}{space 3}0.002{col 55}{space 4}-1.170602{col 68}{space 3}-.2574936
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0196005{col 27}{space 2} .0085195{col 38}{space 1}    2.30{col 47}{space 3}0.021{col 55}{space 4} .0029027{col 68}{space 3} .0362984
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2} .0009711{col 27}{space 2} .0061794{col 38}{space 1}    0.16{col 47}{space 3}0.875{col 55}{space 4}-.0111403{col 68}{space 3} .0130825
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0301236{col 27}{space 2} .0410636{col 38}{space 1}    0.73{col 47}{space 3}0.463{col 55}{space 4}-.0503595{col 68}{space 3} .1106068
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.3624051{col 27}{space 2} .1839997{col 38}{space 1}   -1.97{col 47}{space 3}0.049{col 55}{space 4}-.7230379{col 68}{space 3}-.0017723
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .1984592{col 27}{space 2} .0989741{col 38}{space 1}    2.01{col 47}{space 3}0.045{col 55}{space 4} .0044736{col 68}{space 3} .3924448
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0974361{col 27}{space 2} .0296274{col 38}{space 1}   -3.29{col 47}{space 3}0.001{col 55}{space 4}-.1555047{col 68}{space 3}-.0393674
{txt}civilconflict {c |}{col 15}{res}{space 2}-.2704269{col 27}{space 2} .1020617{col 38}{space 1}   -2.65{col 47}{space 3}0.008{col 55}{space 4}-.4704643{col 68}{space 3}-.0703896
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.1245866{col 27}{space 2} .2324946{col 38}{space 1}   -0.54{col 47}{space 3}0.592{col 55}{space 4}-.5802677{col 68}{space 3} .3310944
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.096066{col 27}{space 2} .5603553{col 38}{space 1}   -3.74{col 47}{space 3}0.000{col 55}{space 4}-3.194343{col 68}{space 3}-.9977902
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0066894{col 27}{space 2} .0009831{col 38}{space 1}   -6.80{col 47}{space 3}0.000{col 55}{space 4}-.0086162{col 68}{space 3}-.0047626
{txt}{space 11}ef {c |}{col 15}{res}{space 2}-.3197783{col 27}{space 2}  .215106{col 38}{space 1}   -1.49{col 47}{space 3}0.137{col 55}{space 4}-.7413783{col 68}{space 3} .1018218
{txt}{space 6}relfrac {c |}{col 15}{res}{space 2}-.0621803{col 27}{space 2} .2523282{col 38}{space 1}   -0.25{col 47}{space 3}0.805{col 55}{space 4}-.5567346{col 68}{space 3} .4323739
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.358469{col 27}{space 2} .2753415{col 38}{space 1}    4.93{col 47}{space 3}0.000{col 55}{space 4} .8188095{col 68}{space 3} 1.898128
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.131959{col 27}{space 2} .3422214{col 38}{space 1}    9.15{col 47}{space 3}0.000{col 55}{space 4} 2.461218{col 68}{space 3} 3.802701
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.504518{col 27}{space 2} .5259631{col 38}{space 1}    8.56{col 47}{space 3}0.000{col 55}{space 4} 3.473649{col 68}{space 3} 5.535387
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1976234{col 27}{space 2} .0337329{col 38}{space 1}   -5.86{col 47}{space 3}0.000{col 55}{space 4}-.2637386{col 68}{space 3}-.1315081
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0022754{col 27}{space 2}  .007635{col 38}{space 1}    0.30{col 47}{space 3}0.766{col 55}{space 4} -.012689{col 68}{space 3} .0172397
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2550548{col 27}{space 2} .1149227{col 38}{space 1}   -2.22{col 47}{space 3}0.026{col 55}{space 4}-.4802991{col 68}{space 3}-.0298105
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000165{col 27}{space 2} .0000187{col 38}{space 1}    0.88{col 47}{space 3}0.380{col 55}{space 4}-.0000203{col 68}{space 3} .0000532
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0518894{col 27}{space 2} .1077515{col 38}{space 1}   -0.48{col 47}{space 3}0.630{col 55}{space 4}-.2630784{col 68}{space 3} .1592996
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0191304{col 27}{space 2} .0225745{col 38}{space 1}   -0.85{col 47}{space 3}0.397{col 55}{space 4}-.0633755{col 68}{space 3} .0251148
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .2367456{col 27}{space 2} .1260916{col 38}{space 1}    1.88{col 47}{space 3}0.060{col 55}{space 4}-.0103894{col 68}{space 3} .4838805
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8834763{col 27}{space 2} .2593409{col 38}{space 1}    3.41{col 47}{space 3}0.001{col 55}{space 4} .3751775{col 68}{space 3} 1.391775
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0750834{col 27}{space 2} .1838862{col 38}{space 1}    0.41{col 47}{space 3}0.683{col 55}{space 4}-.2853268{col 68}{space 3} .4354937
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4571228{col 27}{space 2} .2073704{col 38}{space 1}    2.20{col 47}{space 3}0.027{col 55}{space 4} .0506843{col 68}{space 3} .8635612
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2}  .953784{col 27}{space 2} .2937674{col 38}{space 1}    3.25{col 47}{space 3}0.001{col 55}{space 4} .3780104{col 68}{space 3} 1.529558
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.1962717{col 27}{space 2} .3348326{col 38}{space 1}   -0.59{col 47}{space 3}0.558{col 55}{space 4}-.8525316{col 68}{space 3} .4599881
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2}  .625669{col 27}{space 2} .2224479{col 38}{space 1}    2.81{col 47}{space 3}0.005{col 55}{space 4} .1896792{col 68}{space 3} 1.061659
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1465029{col 27}{space 2} .2513409{col 38}{space 1}    0.58{col 47}{space 3}0.560{col 55}{space 4}-.3461162{col 68}{space 3}  .639122
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 1.049458{col 27}{space 2} 1.013919{col 38}{space 1}    1.04{col 47}{space 3}0.301{col 55}{space 4}-.9377871{col 68}{space 3} 3.036704
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .4685527{col 27}{space 2} .1572285{col 38}{space 1}    2.98{col 47}{space 3}0.003{col 55}{space 4} .1603905{col 68}{space 3} .7767149
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2}-17.76287{col 27}{space 2} 1.709648{col 38}{space 1}  -10.39{col 47}{space 3}0.000{col 55}{space 4}-21.11372{col 68}{space 3}-14.41202
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2}-14.62758{col 27}{space 2} 1.702468{col 38}{space 1}   -8.59{col 47}{space 3}0.000{col 55}{space 4}-17.96436{col 68}{space 3} -11.2908
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2}-12.02081{col 27}{space 2} 1.762898{col 38}{space 1}   -6.82{col 47}{space 3}0.000{col 55}{space 4}-15.47602{col 68}{space 3}-8.565593
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .4370292{col 27}{space 2} .1271987{col 55}{space 4} .1590292{col 68}{space 3} .6508171
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wopol = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop civilconflict nafrme lagwopolglobe trend ef relfrac lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res}-656.86955
{txt}Iteration 2:   log likelihood = {res}-600.70122
{txt}Iteration 3:   log likelihood = {res}-597.48906
{txt}Iteration 4:   log likelihood = {res}-597.46623
{txt}Iteration 5:   log likelihood = {res}-597.46623

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}16{txt}){col 67}= {res}   1473.42
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-597.46623{txt}{col 51}Pseudo R2{col 67}= {res}    0.5522

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0570579{col 27}{space 2} .0882603{col 38}{space 1}   -0.65{col 47}{space 3}0.518{col 55}{space 4} -.230045{col 68}{space 3} .1159292
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}  .008382{col 27}{space 2} .0075256{col 38}{space 1}    1.11{col 47}{space 3}0.265{col 55}{space 4}-.0063679{col 68}{space 3}  .023132
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0346211{col 27}{space 2} .0090779{col 38}{space 1}   -3.81{col 47}{space 3}0.000{col 55}{space 4}-.0524135{col 68}{space 3}-.0168288
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0084302{col 27}{space 2} .0496666{col 38}{space 1}    0.17{col 47}{space 3}0.865{col 55}{space 4}-.0889145{col 68}{space 3} .1057749
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2} -.024496{col 27}{space 2}  .262016{col 38}{space 1}   -0.09{col 47}{space 3}0.926{col 55}{space 4}-.5380379{col 68}{space 3} .4890458
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2551176{col 27}{space 2} .1072211{col 38}{space 1}    2.38{col 47}{space 3}0.017{col 55}{space 4}  .044968{col 68}{space 3} .4652671
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0153246{col 27}{space 2} .0314273{col 38}{space 1}   -0.49{col 47}{space 3}0.626{col 55}{space 4} -.076921{col 68}{space 3} .0462718
{txt}civilconflict {c |}{col 15}{res}{space 2} -.129456{col 27}{space 2} .1043082{col 38}{space 1}   -1.24{col 47}{space 3}0.215{col 55}{space 4}-.3338963{col 68}{space 3} .0749842
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.5253523{col 27}{space 2} .1502375{col 38}{space 1}   -3.50{col 47}{space 3}0.000{col 55}{space 4}-.8198123{col 68}{space 3}-.2308922
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.169713{col 27}{space 2}   .85227{col 38}{space 1}   -1.37{col 47}{space 3}0.170{col 55}{space 4}-2.840132{col 68}{space 3} .5007054
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0480215{col 27}{space 2} .0197319{col 38}{space 1}    2.43{col 47}{space 3}0.015{col 55}{space 4} .0093476{col 68}{space 3} .0866954
{txt}{space 11}ef {c |}{col 15}{res}{space 2}-.2272522{col 27}{space 2} .1835151{col 38}{space 1}   -1.24{col 47}{space 3}0.216{col 55}{space 4}-.5869353{col 68}{space 3} .1324309
{txt}{space 6}relfrac {c |}{col 15}{res}{space 2}-.3243141{col 27}{space 2} .2449148{col 38}{space 1}   -1.32{col 47}{space 3}0.185{col 55}{space 4}-.8043382{col 68}{space 3} .1557101
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.168033{col 27}{space 2} .1735432{col 38}{space 1}    6.73{col 47}{space 3}0.000{col 55}{space 4} .8278945{col 68}{space 3} 1.508171
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2}  3.50775{col 27}{space 2} .1872588{col 38}{space 1}   18.73{col 47}{space 3}0.000{col 55}{space 4}  3.14073{col 68}{space 3} 3.874771
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.805023{col 27}{space 2} .4811221{col 38}{space 1}   14.14{col 47}{space 3}0.000{col 55}{space 4} 5.862041{col 68}{space 3} 7.748005
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 92.91244{col 27}{space 2} 38.01151{col 55}{space 4} 18.41126{col 68}{space 3} 167.4136
{txt}        /cut2 {c |}{col 15}{res}{space 2} 95.34909{col 27}{space 2} 38.01869{col 55}{space 4} 20.83383{col 68}{space 3} 169.8643
{txt}        /cut3 {c |}{col 15}{res}{space 2} 99.57035{col 27}{space 2}  38.0308{col 55}{space 4} 25.03135{col 68}{space 3} 174.1094
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 4163.1302.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}  22495.37
{txt}Log pseudolikelihood = {res}-1883.5184{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.3264489{col 27}{space 2}  .218513{col 38}{space 1}   -1.49{col 47}{space 3}0.135{col 55}{space 4}-.7547265{col 68}{space 3} .1018286
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0090691{col 27}{space 2}  .006903{col 38}{space 1}    1.31{col 47}{space 3}0.189{col 55}{space 4}-.0044606{col 68}{space 3} .0225987
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0381846{col 27}{space 2} .0095369{col 38}{space 1}   -4.00{col 47}{space 3}0.000{col 55}{space 4}-.0568767{col 68}{space 3}-.0194926
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2}-.0078793{col 27}{space 2} .0459378{col 38}{space 1}   -0.17{col 47}{space 3}0.864{col 55}{space 4}-.0979158{col 68}{space 3} .0821572
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2} -.008053{col 27}{space 2} .2941066{col 38}{space 1}   -0.03{col 47}{space 3}0.978{col 55}{space 4}-.5844914{col 68}{space 3} .5683855
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2453153{col 27}{space 2} .1070765{col 38}{space 1}    2.29{col 47}{space 3}0.022{col 55}{space 4} .0354492{col 68}{space 3} .4551814
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0183015{col 27}{space 2} .0373203{col 38}{space 1}   -0.49{col 47}{space 3}0.624{col 55}{space 4} -.091448{col 68}{space 3}  .054845
{txt}civilconflict {c |}{col 15}{res}{space 2} -.164091{col 27}{space 2} .1087023{col 38}{space 1}   -1.51{col 47}{space 3}0.131{col 55}{space 4}-.3771435{col 68}{space 3} .0489615
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.5664206{col 27}{space 2} .1676116{col 38}{space 1}   -3.38{col 47}{space 3}0.001{col 55}{space 4}-.8949333{col 68}{space 3} -.237908
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.267284{col 27}{space 2} .4079882{col 38}{space 1}   -3.11{col 47}{space 3}0.002{col 55}{space 4}-2.066926{col 68}{space 3}-.4676413
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0531288{col 27}{space 2} .0006008{col 38}{space 1}   88.43{col 47}{space 3}0.000{col 55}{space 4} .0519512{col 68}{space 3} .0543064
{txt}{space 11}ef {c |}{col 15}{res}{space 2} -.182059{col 27}{space 2}  .216061{col 38}{space 1}   -0.84{col 47}{space 3}0.399{col 55}{space 4}-.6055307{col 68}{space 3} .2414127
{txt}{space 6}relfrac {c |}{col 15}{res}{space 2}-.3483534{col 27}{space 2} .2610963{col 38}{space 1}   -1.33{col 47}{space 3}0.182{col 55}{space 4}-.8600928{col 68}{space 3} .1633859
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.153473{col 27}{space 2} .3189367{col 38}{space 1}    3.62{col 47}{space 3}0.000{col 55}{space 4} .5283689{col 68}{space 3} 1.778578
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.475171{col 27}{space 2}  .378438{col 38}{space 1}    9.18{col 47}{space 3}0.000{col 55}{space 4} 2.733447{col 68}{space 3} 4.216896
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.725894{col 27}{space 2} .5672486{col 38}{space 1}   11.86{col 47}{space 3}0.000{col 55}{space 4} 5.614107{col 68}{space 3} 7.837681
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2} -.196805{col 27}{space 2} .0334394{col 38}{space 1}   -5.89{col 47}{space 3}0.000{col 55}{space 4} -.262345{col 68}{space 3}-.1312649
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2}  .001778{col 27}{space 2} .0076701{col 38}{space 1}    0.23{col 47}{space 3}0.817{col 55}{space 4} -.013255{col 68}{space 3} .0168111
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2478216{col 27}{space 2} .1154702{col 38}{space 1}   -2.15{col 47}{space 3}0.032{col 55}{space 4} -.474139{col 68}{space 3}-.0215041
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000141{col 27}{space 2} .0000199{col 38}{space 1}    0.71{col 47}{space 3}0.481{col 55}{space 4} -.000025{col 68}{space 3} .0000531
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2} -.041991{col 27}{space 2} .1067143{col 38}{space 1}   -0.39{col 47}{space 3}0.694{col 55}{space 4}-.2511472{col 68}{space 3} .1671651
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0159282{col 27}{space 2} .0224431{col 38}{space 1}   -0.71{col 47}{space 3}0.478{col 55}{space 4}-.0599157{col 68}{space 3} .0280594
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2}  .195023{col 27}{space 2} .1215366{col 38}{space 1}    1.60{col 47}{space 3}0.109{col 55}{space 4}-.0431843{col 68}{space 3} .4332303
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8408076{col 27}{space 2} .2735666{col 38}{space 1}    3.07{col 47}{space 3}0.002{col 55}{space 4}  .304627{col 68}{space 3} 1.376988
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0365648{col 27}{space 2} .1880772{col 38}{space 1}    0.19{col 47}{space 3}0.846{col 55}{space 4}-.3320598{col 68}{space 3} .4051893
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4637268{col 27}{space 2} .2119408{col 38}{space 1}    2.19{col 47}{space 3}0.029{col 55}{space 4} .0483305{col 68}{space 3} .8791232
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9326714{col 27}{space 2} .3019565{col 38}{space 1}    3.09{col 47}{space 3}0.002{col 55}{space 4} .3408476{col 68}{space 3} 1.524495
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.2101713{col 27}{space 2} .3481474{col 38}{space 1}   -0.60{col 47}{space 3}0.546{col 55}{space 4}-.8925276{col 68}{space 3}  .472185
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6097185{col 27}{space 2} .2236052{col 38}{space 1}    2.73{col 47}{space 3}0.006{col 55}{space 4} .1714604{col 68}{space 3} 1.047977
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1214523{col 27}{space 2} .2598371{col 38}{space 1}    0.47{col 47}{space 3}0.640{col 55}{space 4}-.3878191{col 68}{space 3} .6307238
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .9977455{col 27}{space 2} 1.024598{col 38}{space 1}    0.97{col 47}{space 3}0.330{col 55}{space 4}-1.010429{col 68}{space 3}  3.00592
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1778049{col 27}{space 2} .1254327{col 38}{space 1}    1.42{col 47}{space 3}0.156{col 55}{space 4}-.0680387{col 68}{space 3} .4236484
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2}  102.695{col 27}{space 2} .8035485{col 38}{space 1}  127.80{col 47}{space 3}0.000{col 55}{space 4} 101.1201{col 68}{space 3} 104.2699
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 105.1118{col 27}{space 2} .8189563{col 38}{space 1}  128.35{col 47}{space 3}0.000{col 55}{space 4} 103.5066{col 68}{space 3} 106.7169
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 109.2951{col 27}{space 2} .8529422{col 38}{space 1}  128.14{col 47}{space 3}0.000{col 55}{space 4} 107.6233{col 68}{space 3} 110.9668
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1759545{col 27}{space 2} .1215493{col 55}{space 4}-.0679339{col 68}{space 3} .3999996
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *ROBUSTNESS CHECK : Civil war variable dropped
. cmp(wecon = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop nafrme lagweconglobe trend lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1280.5596
{txt}Iteration 1:   log likelihood = {res}-852.91984
{txt}Iteration 2:   log likelihood = {res}-828.82933
{txt}Iteration 3:   log likelihood = {res}-828.13356
{txt}Iteration 4:   log likelihood = {res}-828.13178

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1653
{txt}{col 51}LR chi2({res}13{txt}){col 67}= {res}    904.86
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-828.13178{txt}{col 51}Pseudo R2{col 67}= {res}    0.3533

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0741839{col 27}{space 2} .0753269{col 38}{space 1}   -0.98{col 47}{space 3}0.325{col 55}{space 4}-.2218219{col 68}{space 3}  .073454
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0197731{col 27}{space 2} .0063872{col 38}{space 1}    3.10{col 47}{space 3}0.002{col 55}{space 4} .0072544{col 68}{space 3} .0322918
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}  .007986{col 27}{space 2} .0062799{col 38}{space 1}    1.27{col 47}{space 3}0.203{col 55}{space 4}-.0043224{col 68}{space 3} .0202943
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2}  .098017{col 27}{space 2}  .041054{col 38}{space 1}    2.39{col 47}{space 3}0.017{col 55}{space 4} .0175526{col 68}{space 3} .1784814
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.4050641{col 27}{space 2} .2091581{col 38}{space 1}   -1.94{col 47}{space 3}0.053{col 55}{space 4}-.8150064{col 68}{space 3} .0048782
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2}  .278858{col 27}{space 2} .0977815{col 38}{space 1}    2.85{col 47}{space 3}0.004{col 55}{space 4} .0872098{col 68}{space 3} .4705063
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0986534{col 27}{space 2} .0249766{col 38}{space 1}   -3.95{col 47}{space 3}0.000{col 55}{space 4}-.1476067{col 68}{space 3}-.0497001
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2} .0272318{col 27}{space 2} .1199961{col 38}{space 1}    0.23{col 47}{space 3}0.820{col 55}{space 4}-.2079563{col 68}{space 3} .2624199
{txt}lagweconglobe {c |}{col 15}{res}{space 2} -2.10701{col 27}{space 2} .5112026{col 38}{space 1}   -4.12{col 47}{space 3}0.000{col 55}{space 4}-3.108948{col 68}{space 3}-1.105071
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0177928{col 27}{space 2} .0075243{col 38}{space 1}   -2.36{col 47}{space 3}0.018{col 55}{space 4}-.0325401{col 68}{space 3}-.0030455
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.469037{col 27}{space 2} .1350841{col 38}{space 1}   10.87{col 47}{space 3}0.000{col 55}{space 4} 1.204277{col 68}{space 3} 1.733796
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.358948{col 27}{space 2}  .159767{col 38}{space 1}   21.02{col 47}{space 3}0.000{col 55}{space 4}  3.04581{col 68}{space 3} 3.672085
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.856954{col 27}{space 2} .4325611{col 38}{space 1}   11.23{col 47}{space 3}0.000{col 55}{space 4} 4.009149{col 68}{space 3} 5.704758
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} -38.9137{col 27}{space 2} 14.72248{col 55}{space 4}-67.76923{col 68}{space 3}-10.05817
{txt}        /cut2 {c |}{col 15}{res}{space 2}-35.65453{col 27}{space 2} 14.71198{col 55}{space 4}-64.48948{col 68}{space 3}-6.819568
{txt}        /cut3 {c |}{col 15}{res}{space 2}-32.94979{col 27}{space 2} 14.71096{col 55}{space 4}-61.78274{col 68}{space 3} -4.11684
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 4852.4992.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}13{txt}){col 67}= {res}    641.77
{txt}Log pseudolikelihood = {res}-2109.8898{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.6827381{col 27}{space 2} .2418753{col 38}{space 1}   -2.82{col 47}{space 3}0.005{col 55}{space 4}-1.156805{col 68}{space 3}-.2086711
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}  .020793{col 27}{space 2} .0077952{col 38}{space 1}    2.67{col 47}{space 3}0.008{col 55}{space 4} .0055148{col 68}{space 3} .0360712
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}  .001228{col 27}{space 2} .0072181{col 38}{space 1}    0.17{col 47}{space 3}0.865{col 55}{space 4}-.0129192{col 68}{space 3} .0153752
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0628112{col 27}{space 2} .0416171{col 38}{space 1}    1.51{col 47}{space 3}0.131{col 55}{space 4}-.0187569{col 68}{space 3} .1443792
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.3640734{col 27}{space 2} .1829025{col 38}{space 1}   -1.99{col 47}{space 3}0.047{col 55}{space 4}-.7225557{col 68}{space 3}-.0055912
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .2369482{col 27}{space 2} .1083787{col 38}{space 1}    2.19{col 47}{space 3}0.029{col 55}{space 4} .0245298{col 68}{space 3} .4493666
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.1060275{col 27}{space 2} .0257763{col 38}{space 1}   -4.11{col 47}{space 3}0.000{col 55}{space 4}-.1565481{col 68}{space 3} -.055507
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.0683618{col 27}{space 2}  .211364{col 38}{space 1}   -0.32{col 47}{space 3}0.746{col 55}{space 4}-.4826277{col 68}{space 3} .3459041
{txt}lagweconglobe {c |}{col 15}{res}{space 2}-2.124015{col 27}{space 2} .5642808{col 38}{space 1}   -3.76{col 47}{space 3}0.000{col 55}{space 4}-3.229985{col 68}{space 3}-1.018045
{txt}{space 8}trend {c |}{col 15}{res}{space 2}-.0097517{col 27}{space 2} .0010645{col 38}{space 1}   -9.16{col 47}{space 3}0.000{col 55}{space 4}-.0118381{col 68}{space 3}-.0076654
{txt}{space 6}lwecon1 {c |}{col 15}{res}{space 2} 1.406617{col 27}{space 2} .2843043{col 38}{space 1}    4.95{col 47}{space 3}0.000{col 55}{space 4} .8493908{col 68}{space 3} 1.963843
{txt}{space 6}lwecon2 {c |}{col 15}{res}{space 2} 3.197222{col 27}{space 2} .3522958{col 38}{space 1}    9.08{col 47}{space 3}0.000{col 55}{space 4} 2.506734{col 68}{space 3} 3.887709
{txt}{space 6}lwecon3 {c |}{col 15}{res}{space 2} 4.616056{col 27}{space 2} .5221433{col 38}{space 1}    8.84{col 47}{space 3}0.000{col 55}{space 4} 3.592674{col 68}{space 3} 5.639438
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1969706{col 27}{space 2} .0337605{col 38}{space 1}   -5.83{col 47}{space 3}0.000{col 55}{space 4}-.2631399{col 68}{space 3}-.1308013
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0023649{col 27}{space 2} .0076778{col 38}{space 1}    0.31{col 47}{space 3}0.758{col 55}{space 4}-.0126833{col 68}{space 3} .0174131
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2221114{col 27}{space 2} .1169631{col 38}{space 1}   -1.90{col 47}{space 3}0.058{col 55}{space 4}-.4513549{col 68}{space 3} .0071321
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2}  .000017{col 27}{space 2} .0000189{col 38}{space 1}    0.90{col 47}{space 3}0.369{col 55}{space 4}-.0000201{col 68}{space 3} .0000541
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0435623{col 27}{space 2} .1081704{col 38}{space 1}   -0.40{col 47}{space 3}0.687{col 55}{space 4}-.2555724{col 68}{space 3} .1684479
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0129944{col 27}{space 2} .0226173{col 38}{space 1}   -0.57{col 47}{space 3}0.566{col 55}{space 4}-.0573235{col 68}{space 3} .0313347
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .2334835{col 27}{space 2} .1258604{col 38}{space 1}    1.86{col 47}{space 3}0.064{col 55}{space 4}-.0131984{col 68}{space 3} .4801654
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2}  .871186{col 27}{space 2} .2636166{col 38}{space 1}    3.30{col 47}{space 3}0.001{col 55}{space 4}  .354507{col 68}{space 3} 1.387865
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0800712{col 27}{space 2}  .185819{col 38}{space 1}    0.43{col 47}{space 3}0.667{col 55}{space 4}-.2841274{col 68}{space 3} .4442699
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4652485{col 27}{space 2} .2088308{col 38}{space 1}    2.23{col 47}{space 3}0.026{col 55}{space 4} .0559476{col 68}{space 3} .8745493
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9531467{col 27}{space 2} .2955999{col 38}{space 1}    3.22{col 47}{space 3}0.001{col 55}{space 4} .3737816{col 68}{space 3} 1.532512
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2}-.1828504{col 27}{space 2} .3404887{col 38}{space 1}   -0.54{col 47}{space 3}0.591{col 55}{space 4} -.850196{col 68}{space 3} .4844953
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2}  .635724{col 27}{space 2}   .22196{col 38}{space 1}    2.86{col 47}{space 3}0.004{col 55}{space 4} .2006903{col 68}{space 3} 1.070758
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1482566{col 27}{space 2} .2515775{col 38}{space 1}    0.59{col 47}{space 3}0.556{col 55}{space 4}-.3448263{col 68}{space 3} .6413395
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .7569036{col 27}{space 2} 1.032958{col 38}{space 1}    0.73{col 47}{space 3}0.464{col 55}{space 4}-1.267658{col 68}{space 3} 2.781465
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .4360777{col 27}{space 2} .1671803{col 38}{space 1}    2.61{col 47}{space 3}0.009{col 55}{space 4} .1084104{col 68}{space 3}  .763745
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} -23.4812{col 27}{space 2} 1.908401{col 38}{space 1}  -12.30{col 47}{space 3}0.000{col 55}{space 4} -27.2216{col 68}{space 3}-19.74081
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2}-20.35472{col 27}{space 2} 1.903664{col 38}{space 1}  -10.69{col 47}{space 3}0.000{col 55}{space 4}-24.08583{col 68}{space 3}-16.62361
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} -17.7535{col 27}{space 2} 1.990669{col 38}{space 1}   -8.92{col 47}{space 3}0.000{col 55}{space 4}-21.65514{col 68}{space 3}-13.85186
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2}  .410388{col 27}{space 2} .1390241{col 55}{space 4} .1079876{col 68}{space 3} .6432776
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. cmp(wopol = imfdummy polity2 gdpecon indexipo Dindexipo cedawdummy lntotalfempop nafrme lagwopolglobe trend lwopol1 lwopol2 lwopol3) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1334.1773
{txt}Iteration 1:   log likelihood = {res} -658.7282
{txt}Iteration 2:   log likelihood = {res}-603.65902
{txt}Iteration 3:   log likelihood = {res}-600.65102
{txt}Iteration 4:   log likelihood = {res}-600.63149
{txt}Iteration 5:   log likelihood = {res}-600.63149

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1680
{txt}{col 51}LR chi2({res}13{txt}){col 67}= {res}   1467.09
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-600.63149{txt}{col 51}Pseudo R2{col 67}= {res}    0.5498

{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      _cmp_y1{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.0664605{col 27}{space 2} .0873469{col 38}{space 1}   -0.76{col 47}{space 3}0.447{col 55}{space 4}-.2376573{col 68}{space 3} .1047363
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}  .011291{col 27}{space 2} .0071974{col 38}{space 1}    1.57{col 47}{space 3}0.117{col 55}{space 4}-.0028157{col 68}{space 3} .0253977
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0349192{col 27}{space 2} .0088884{col 38}{space 1}   -3.93{col 47}{space 3}0.000{col 55}{space 4}-.0523401{col 68}{space 3}-.0174984
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0421306{col 27}{space 2} .0477642{col 38}{space 1}    0.88{col 47}{space 3}0.378{col 55}{space 4}-.0514856{col 68}{space 3} .1357468
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0751693{col 27}{space 2} .2585017{col 38}{space 1}   -0.29{col 47}{space 3}0.771{col 55}{space 4}-.5818233{col 68}{space 3} .4314848
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2} .3091382{col 27}{space 2} .1037941{col 38}{space 1}    2.98{col 47}{space 3}0.003{col 55}{space 4} .1057054{col 68}{space 3} .5125709
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0079968{col 27}{space 2} .0296588{col 38}{space 1}   -0.27{col 47}{space 3}0.787{col 55}{space 4} -.066127{col 68}{space 3} .0501334
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.3778155{col 27}{space 2} .1247249{col 38}{space 1}   -3.03{col 47}{space 3}0.002{col 55}{space 4}-.6222717{col 68}{space 3}-.1333592
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.175119{col 27}{space 2} .8501797{col 38}{space 1}   -1.38{col 47}{space 3}0.167{col 55}{space 4} -2.84144{col 68}{space 3} .4912029
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0417181{col 27}{space 2} .0194615{col 38}{space 1}    2.14{col 47}{space 3}0.032{col 55}{space 4} .0035742{col 68}{space 3}  .079862
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.222538{col 27}{space 2} .1713985{col 38}{space 1}    7.13{col 47}{space 3}0.000{col 55}{space 4}  .886603{col 68}{space 3} 1.558473
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2}  3.57021{col 27}{space 2} .1848787{col 38}{space 1}   19.31{col 47}{space 3}0.000{col 55}{space 4} 3.207855{col 68}{space 3} 3.932566
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.838965{col 27}{space 2} .4822924{col 38}{space 1}   14.18{col 47}{space 3}0.000{col 55}{space 4} 5.893689{col 68}{space 3}  7.78424
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        /cut1 {c |}{col 15}{res}{space 2} 81.07006{col 27}{space 2} 37.51408{col 55}{space 4} 7.543822{col 68}{space 3} 154.5963
{txt}        /cut2 {c |}{col 15}{res}{space 2} 83.50121{col 27}{space 2} 37.52097{col 55}{space 4} 9.961462{col 68}{space 3}  157.041
{txt}        /cut3 {c |}{col 15}{res}{space 2} 87.69318{col 27}{space 2} 37.53058{col 55}{space 4} 14.13459{col 68}{space 3} 161.2518
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 3316.832.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}13{txt}){col 67}= {res}  22544.95
{txt}Log pseudolikelihood = {res}-1886.9342{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 79:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wopol         {txt}{c |}
{space 5}imfdummy {c |}{col 15}{res}{space 2}-.2706768{col 27}{space 2} .2024967{col 38}{space 1}   -1.34{col 47}{space 3}0.181{col 55}{space 4} -.667563{col 68}{space 3} .1262094
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2} .0116027{col 27}{space 2} .0064166{col 38}{space 1}    1.81{col 47}{space 3}0.071{col 55}{space 4}-.0009737{col 68}{space 3}  .024179
{txt}{space 6}gdpecon {c |}{col 15}{res}{space 2}-.0376248{col 27}{space 2} .0096936{col 38}{space 1}   -3.88{col 47}{space 3}0.000{col 55}{space 4} -.056624{col 68}{space 3}-.0186257
{txt}{space 5}indexipo {c |}{col 15}{res}{space 2} .0306082{col 27}{space 2} .0469757{col 38}{space 1}    0.65{col 47}{space 3}0.515{col 55}{space 4}-.0614624{col 68}{space 3} .1226788
{txt}{space 4}Dindexipo {c |}{col 15}{res}{space 2}-.0685852{col 27}{space 2} .2947032{col 38}{space 1}   -0.23{col 47}{space 3}0.816{col 55}{space 4}-.6461928{col 68}{space 3} .5090225
{txt}{space 3}cedawdummy {c |}{col 15}{res}{space 2}  .299242{col 27}{space 2}  .100027{col 38}{space 1}    2.99{col 47}{space 3}0.003{col 55}{space 4} .1031926{col 68}{space 3} .4952914
{txt}lntotalfempop {c |}{col 15}{res}{space 2}-.0120723{col 27}{space 2} .0348563{col 38}{space 1}   -0.35{col 47}{space 3}0.729{col 55}{space 4}-.0803894{col 68}{space 3} .0562448
{txt}{space 7}nafrme {c |}{col 15}{res}{space 2}-.4139374{col 27}{space 2} .1302803{col 38}{space 1}   -3.18{col 47}{space 3}0.001{col 55}{space 4}-.6692821{col 68}{space 3}-.1585926
{txt}lagwopolglobe {c |}{col 15}{res}{space 2}-1.245467{col 27}{space 2} .3943757{col 38}{space 1}   -3.16{col 47}{space 3}0.002{col 55}{space 4}-2.018429{col 68}{space 3}-.4725047
{txt}{space 8}trend {c |}{col 15}{res}{space 2} .0457596{col 27}{space 2} .0005421{col 38}{space 1}   84.41{col 47}{space 3}0.000{col 55}{space 4} .0446971{col 68}{space 3} .0468221
{txt}{space 6}lwopol1 {c |}{col 15}{res}{space 2} 1.216149{col 27}{space 2} .3144224{col 38}{space 1}    3.87{col 47}{space 3}0.000{col 55}{space 4} .5998928{col 68}{space 3} 1.832406
{txt}{space 6}lwopol2 {c |}{col 15}{res}{space 2} 3.551596{col 27}{space 2}  .371051{col 38}{space 1}    9.57{col 47}{space 3}0.000{col 55}{space 4}  2.82435{col 68}{space 3} 4.278843
{txt}{space 6}lwopol3 {c |}{col 15}{res}{space 2} 6.799141{col 27}{space 2}  .551511{col 38}{space 1}   12.33{col 47}{space 3}0.000{col 55}{space 4} 5.718199{col 68}{space 3} 7.880083
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy      {txt}{c |}
{space 6}gdpecon {c |}{col 15}{res}{space 2}-.1962592{col 27}{space 2}  .033429{col 38}{space 1}   -5.87{col 47}{space 3}0.000{col 55}{space 4}-.2617789{col 68}{space 3}-.1307395
{txt}{space 4}gdpgrowth {c |}{col 15}{res}{space 2} .0017922{col 27}{space 2} .0076753{col 38}{space 1}    0.23{col 47}{space 3}0.815{col 55}{space 4}-.0132511{col 68}{space 3} .0168355
{txt}{space 2}currencynew {c |}{col 15}{res}{space 2}-.2423639{col 27}{space 2} .1159875{col 38}{space 1}   -2.09{col 47}{space 3}0.037{col 55}{space 4}-.4696952{col 68}{space 3}-.0150326
{txt}{space 5}exchrate {c |}{col 15}{res}{space 2} .0000142{col 27}{space 2}   .00002{col 38}{space 1}    0.71{col 47}{space 3}0.476{col 55}{space 4}-.0000249{col 68}{space 3} .0000533
{txt}{space 5}tradelog {c |}{col 15}{res}{space 2}-.0404968{col 27}{space 2} .1070596{col 38}{space 1}   -0.38{col 47}{space 3}0.705{col 55}{space 4}-.2503298{col 68}{space 3} .1693362
{txt}{space 6}polity2 {c |}{col 15}{res}{space 2}-.0149789{col 27}{space 2} .0225858{col 38}{space 1}   -0.66{col 47}{space 3}0.507{col 55}{space 4}-.0592463{col 68}{space 3} .0292886
{txt}{space 6}coldwar {c |}{col 15}{res}{space 2} .1928227{col 27}{space 2}  .121267{col 38}{space 1}    1.59{col 47}{space 3}0.112{col 55}{space 4}-.0448562{col 68}{space 3} .4305016
{txt}{space 3}usalliance {c |}{col 15}{res}{space 2} .8410216{col 27}{space 2} .2742554{col 38}{space 1}    3.07{col 47}{space 3}0.002{col 55}{space 4}  .303491{col 68}{space 3} 1.378552
{txt}{space 6}colbrit {c |}{col 15}{res}{space 2} .0397294{col 27}{space 2} .1884039{col 38}{space 1}    0.21{col 47}{space 3}0.833{col 55}{space 4}-.3295354{col 68}{space 3} .4089942
{txt}{space 7}colfra {c |}{col 15}{res}{space 2} .4644835{col 27}{space 2}  .212453{col 38}{space 1}    2.19{col 47}{space 3}0.029{col 55}{space 4} .0480831{col 68}{space 3} .8808838
{txt}{space 7}eeurop {c |}{col 15}{res}{space 2} .9329322{col 27}{space 2} .3020833{col 38}{space 1}    3.09{col 47}{space 3}0.002{col 55}{space 4} .3408598{col 68}{space 3} 1.525005
{txt}{space 5}lamerica {c |}{col 15}{res}{space 2} -.211523{col 27}{space 2} .3486998{col 38}{space 1}   -0.61{col 47}{space 3}0.544{col 55}{space 4} -.894962{col 68}{space 3} .4719161
{txt}{space 5}ssafrica {c |}{col 15}{res}{space 2} .6107538{col 27}{space 2} .2231963{col 38}{space 1}    2.74{col 47}{space 3}0.006{col 55}{space 4}  .173297{col 68}{space 3} 1.048211
{txt}{space 9}asia {c |}{col 15}{res}{space 2} .1178094{col 27}{space 2} .2588636{col 38}{space 1}    0.46{col 47}{space 3}0.649{col 55}{space 4} -.389554{col 68}{space 3} .6251727
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .9506973{col 27}{space 2} 1.033303{col 38}{space 1}    0.92{col 47}{space 3}0.358{col 55}{space 4}-1.074539{col 68}{space 3} 2.975934
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
 /atanhrho_12 {c |}{col 15}{res}{space 2} .1358815{col 27}{space 2} .1201313{col 38}{space 1}    1.13{col 47}{space 3}0.258{col 55}{space 4}-.0995715{col 68}{space 3} .3713345
{txt}     /cut_1_1 {c |}{col 15}{res}{space 2} 88.79694{col 27}{space 2} .6767567{col 38}{space 1}  131.21{col 47}{space 3}0.000{col 55}{space 4} 87.47052{col 68}{space 3} 90.12336
{txt}     /cut_1_2 {c |}{col 15}{res}{space 2} 91.21571{col 27}{space 2} .6738254{col 38}{space 1}  135.37{col 47}{space 3}0.000{col 55}{space 4} 89.89504{col 68}{space 3} 92.53639
{txt}     /cut_1_3 {c |}{col 15}{res}{space 2} 95.38568{col 27}{space 2} .6900137{col 38}{space 1}  138.24{col 47}{space 3}0.000{col 55}{space 4} 94.03328{col 68}{space 3} 96.73808
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       rho_12{col 15}{c |}{res}{space 2} .1350514{col 27}{space 2} .1179402{col 55}{space 4}-.0992437{col 68}{space 3} .3551584
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. * CORRELATION MATRIX
. cmp(wecon = wopol imfdummy polity2 gdpecon liberalization Dliberalization cedawdummy lntotalfempop civilconflict nafrme  lagweconglobe lagwopolglobe trend lwecon1 lwecon2 lwecon3 ) (imfdummy = gdpecon gdpgrowth currency exchrate tradelog polity2 coldwar usalliance colbrit colfra eeurop lamerica ssafrica asia) if year>1980, nolr ind($cmp_oprobit $cmp_probit) robust quietly cluster(ccode)
{res}
Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
      For exact fits of each equation alone, run cmp separately on each.

{txt}Iteration 0:   log likelihood = {res}-1278.1703
{txt}Iteration 1:   log likelihood = {res}-824.66584
{txt}Iteration 2:   log likelihood = {res}-793.54017
{txt}Iteration 3:   log likelihood = {res}-792.24776
{txt}Iteration 4:   log likelihood = {res}-792.24269

{txt}Ordered probit regression{col 51}Number of obs{col 67}= {res}      1646
{txt}{col 51}LR chi2({res}16{txt}){col 67}= {res}    971.86
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-792.24269{txt}{col 51}Pseudo R2{col 67}= {res}    0.3802

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        _cmp_y1{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}wopol {c |}{col 17}{res}{space 2} .5953313{col 29}{space 2} .0783896{col 40}{space 1}    7.59{col 49}{space 3}0.000{col 57}{space 4} .4416905{col 70}{space 3}  .748972
{txt}{space 7}imfdummy {c |}{col 17}{res}{space 2}-.0367246{col 29}{space 2} .0770661{col 40}{space 1}   -0.48{col 49}{space 3}0.634{col 57}{space 4}-.1877713{col 70}{space 3} .1143222
{txt}{space 8}polity2 {c |}{col 17}{res}{space 2} .0207138{col 29}{space 2} .0065955{col 40}{space 1}    3.14{col 49}{space 3}0.002{col 57}{space 4} .0077869{col 70}{space 3} .0336407
{txt}{space 8}gdpecon {c |}{col 17}{res}{space 2} .0221939{col 29}{space 2} .0066678{col 40}{space 1}    3.33{col 49}{space 3}0.001{col 57}{space 4} .0091253{col 70}{space 3} .0352626
{txt}{space 1}liberalization {c |}{col 17}{res}{space 2} .1009927{col 29}{space 2} .0423051{col 40}{space 1}    2.39{col 49}{space 3}0.017{col 57}{space 4} .0180763{col 70}{space 3} .1839092
{txt}Dliberalization {c |}{col 17}{res}{space 2}-.4463835{col 29}{space 2} .2132703{col 40}{space 1}   -2.09{col 49}{space 3}0.036{col 57}{space 4}-.8643857{col 70}{space 3}-.0283814
{txt}{space 5}cedawdummy {c |}{col 17}{res}{space 2} .1506018{col 29}{space 2}  .101573{col 40}{space 1}    1.48{col 49}{space 3}0.138{col 57}{space 4}-.0484776{col 70}{space 3} .3496813
{txt}{space 2}lntotalfempop {c |}{col 17}{res}{space 2} -.092931{col 29}{space 2}  .026166{col 40}{space 1}   -3.55{col 49}{space 3}0.000{col 57}{space 4}-.1442155{col 70}{space 3}-.0416465
{txt}{space 2}civilconflict {c |}{col 17}{res}{space 2}-.1773174{col 29}{space 2} .0954997{col 40}{space 1}   -1.86{col 49}{space 3}0.063{col 57}{space 4}-.3644933{col 70}{space 3} .0098586
{txt}{space 9}nafrme {c |}{col 17}{res}{space 2} .2535386{col 29}{space 2} .1260006{col 40}{space 1}    2.01{col 49}{space 3}0.044{col 57}{space 4} .0065819{col 70}{space 3} .5004953
{txt}{space 2}lagweconglobe {c |}{col 17}{res}{space 2}-2.979607{col 29}{space 2} .6959317{col 40}{space 1}   -4.28{col 49}{space 3}0.000{col 57}{space 4}-4.343608{col 70}{space 3}-1.615606
{txt}{space 2}lagwopolglobe {c |}{col 17}{res}{space 2} 1.798066{col 29}{space 2} 1.039939{col 40}{space 1}    1.73{col 49}{space 3}0.084{col 57}{space 4}-.2401768{col 70}{space 3}  3.83631
{txt}{space 10}trend {c |}{col 17}{res}{space 2}-.0652101{col 29}{space 2} .0220383{col 40}{space 1}   -2.96{col 49}{space 3}0.003{col 57}{space 4}-.1084043{col 70}{space 3}-.0220159
{txt}{space 8}lwecon1 {c |}{col 17}{res}{space 2} 1.361265{col 29}{space 2} .1390173{col 40}{space 1}    9.79{col 49}{space 3}0.000{col 57}{space 4} 1.088796{col 70}{space 3} 1.633734
{txt}{space 8}lwecon2 {c |}{col 17}{res}{space 2} 3.164615{col 29}{space 2} .1641491{col 40}{space 1}   19.28{col 49}{space 3}0.000{col 57}{space 4} 2.842888{col 70}{space 3} 3.486341
{txt}{space 8}lwecon3 {c |}{col 17}{res}{space 2} 4.664687{col 29}{space 2} .4382474{col 40}{space 1}   10.64{col 49}{space 3}0.000{col 57}{space 4} 3.805738{col 70}{space 3} 5.523636
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          /cut1 {c |}{col 17}{res}{space 2}-130.7297{col 29}{space 2} 42.78999{col 57}{space 4}-214.5965{col 70}{space 3}-46.86285
{txt}          /cut2 {c |}{col 17}{res}{space 2}-127.3295{col 29}{space 2}  42.7788{col 57}{space 4}-211.1744{col 70}{space 3}-43.48458
{txt}          /cut3 {c |}{col 17}{res}{space 2}-124.5477{col 29}{space 2}  42.7736{col 57}{space 4}-208.3824{col 70}{space 3}-40.71301
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
Warning: regressor matrix for {txt}_cmp_y1{res} equation appears ill-conditioned. (Condition number = 6372.1196.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

{txt}Iteration 0:   log likelihood = {res}-1489.7917
{txt}Iteration 1:   log likelihood = {res}-1324.1774
{txt}Iteration 2:   log likelihood = {res}-1291.1498
{txt}Iteration 3:   log likelihood = {res}-1286.8449
{txt}Iteration 4:   log likelihood = {res}-1286.8073
{txt}Iteration 5:   log likelihood = {res}-1286.8073

{txt}Probit regression                                 Number of obs   = {res}      2245
                                                  {txt}LR chi2({res}14{txt})     = {res}    405.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log likelihood = {res}-1286.8073                       {txt}Pseudo R2       = {res}    0.1363

{txt}{hline 13}{c TT}{hline 64}
    imfdummy {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
     gdpecon {c |}  {res}-.1952513   .0170509   -11.45   0.000    -.2286704   -.1618322
   {txt}gdpgrowth {c |}  {res} .0017853   .0045608     0.39   0.695    -.0071537    .0107242
 {txt}currencynew {c |}  {res}-.2449211    .059119    -4.14   0.000    -.3607922   -.1290501
    {txt}exchrate {c |}  {res} .0000145   .0000203     0.72   0.475    -.0000253    .0000544
    {txt}tradelog {c |}  {res}-.0404553   .0575377    -0.70   0.482    -.1532271    .0723166
     {txt}polity2 {c |}  {res} -.015677   .0114489    -1.37   0.171    -.0381164    .0067624
     {txt}coldwar {c |}  {res} .1870833   .0687723     2.72   0.007      .052292    .3218745
  {txt}usalliance {c |}  {res} .8416238   .1398461     6.02   0.000     .5675305    1.115717
     {txt}colbrit {c |}  {res} .0368211   .0877927     0.42   0.675    -.1352495    .2088917
      {txt}colfra {c |}  {res} .4613249   .0936167     4.93   0.000     .2778396    .6448102
      {txt}eeurop {c |}  {res} .9266662   .1553843     5.96   0.000     .6221185    1.231214
    {txt}lamerica {c |}  {res}-.2149573   .1711045    -1.26   0.209     -.550316    .1204013
    {txt}ssafrica {c |}  {res} .6033572   .1134309     5.32   0.000     .3810367    .8256776
        {txt}asia {c |}  {res} .1039899    .131554     0.79   0.429    -.1538512    .3618309
       {txt}_cons {c |}  {res} .9837719   .5765244     1.71   0.088    -.1461951    2.113739
{txt}{hline 13}{c BT}{hline 64}
Note: 10 failures and 0 successes completely determined.
{res}
Warning: regressor matrix for {txt}imfdummy{res} equation appears ill-conditioned. (Condition number = 384.6829.)
This {it:might} prevent convergence. If it does, and if you have not done so already, you may need to remove nearly
collinear regressors to achieve convergence. Or you may need to add a {opt nrtol:erance(#)} or {opt nonrtol:erance} option to the command line.
See {help cmp##tips:cmp tips} for more information. 

Fitting full model.

{txt}Mixed-process regression{col 51}Number of obs{col 67}= {res}      2289
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}   4792.47
{txt}Log pseudolikelihood = {res}-2072.8643{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:119} clusters in ccode)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}wecon           {txt}{c |}
{space 10}wopol {c |}{col 17}{res}{space 2}  .557851{col 29}{space 2} .0906029{col 40}{space 1}    6.16{col 49}{space 3}0.000{col 57}{space 4} .3802726{col 70}{space 3} .7354295
{txt}{space 7}imfdummy {c |}{col 17}{res}{space 2}-.7100382{col 29}{space 2} .2298722{col 40}{space 1}   -3.09{col 49}{space 3}0.002{col 57}{space 4}-1.160579{col 70}{space 3}-.2594969
{txt}{space 8}polity2 {c |}{col 17}{res}{space 2} .0222034{col 29}{space 2} .0080718{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} .0063829{col 70}{space 3} .0380239
{txt}{space 8}gdpecon {c |}{col 17}{res}{space 2}  .013574{col 29}{space 2} .0074899{col 40}{space 1}    1.81{col 49}{space 3}0.070{col 57}{space 4}-.0011059{col 70}{space 3} .0282539
{txt}{space 1}liberalization {c |}{col 17}{res}{space 2}  .057059{col 29}{space 2} .0463478{col 40}{space 1}    1.23{col 49}{space 3}0.218{col 57}{space 4} -.033781{col 70}{space 3}  .147899
{txt}Dliberalization {c |}{col 17}{res}{space 2} -.399828{col 29}{space 2}  .185668{col 40}{space 1}   -2.15{col 49}{space 3}0.031{col 57}{space 4}-.7637305{col 70}{space 3}-.0359254
{txt}{space 5}cedawdummy {c |}{col 17}{res}{space 2} .1138595{col 29}{space 2} .1105503{col 40}{space 1}    1.03{col 49}{space 3}0.303{col 57}{space 4}-.1028152{col 70}{space 3} .3305342
{txt}{space 2}lntotalfempop {c |}{col 17}{res}{space 2}-.0957813{col 29}{space 2} .0302649{col 40}{space 1}   -3.16{col 49}{space 3}0.002{col 57}{space 4}-.1550995{col 70}{space 3}-.0364632
{txt}{space 2}civilconflict {c |}{col 17}{res}{space 2} -.252259{col 29}{space 2} .0946644{col 40}{space 1}   -2.66{col 49}{space 3}0.008{col 57}{space 4}-.4377979{col 70}{space 3}-.0667201
{txt}{space 9}nafrme {c |}{col 17}{res}{space 2} .1480377{col 29}{space 2} .1872023{col 40}{space 1}    0.79{col 49}{space 3}0.429{col 57}{space 4}-.2188721{col 70}{space 3} .5149475
{txt}{space 2}lagweconglobe {c |}{col 17}{res}{space 2}-2.814553{col 29}{space 2} .6566345{col 40}{space 1}   -4.29{col 49}{space 3}0.000{col 57}{space 4}-4.101533{col 70}{space 3}-1.527573
{txt}{space 2}lagwopolglobe {c |}{col 17}{res}{space 2} 1.441489{col 29}{space 2} .4254467{col 40}{space 1}    3.39{col 49}{space 3}0.001{col 57}{space 4}  .607629{col 70}{space 3}  2.27535
{txt}{space 10}trend {c |}{col 17}{res}{space 2}-.0490095{col 29}{space 2} .0011157{col 40}{space 1}  -43.93{col 49}{space 3}0.000{col 57}{space 4}-.0511964{col 70}{space 3}-.0468227
{txt}{space 8}lwecon1 {c |}{col 17}{res}{space 2} 1.288919{col 29}{space 2} .2490417{col 40}{space 1}    5.18{col 49}{space 3}0.000{col 57}{space 4}  .800806{col 70}{space 3} 1.777031
{txt}{space 8}lwecon2 {c |}{col 17}{res}{space 2} 2.978643{col 29}{space 2} .3196311{col 40}{space 1}    9.32{col 49}{space 3}0.000{col 57}{space 4} 2.352177{col 70}{space 3} 3.605108
{txt}{space 8}lwecon3 {c |}{col 17}{res}{space 2} 4.372174{col 29}{space 2} .5278205{col 40}{space 1}    8.28{col 49}{space 3}0.000{col 57}{space 4} 3.337665{col 70}{space 3} 5.406683
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}imfdummy        {txt}{c |}
{space 8}gdpecon {c |}{col 17}{res}{space 2}-.1946161{col 29}{space 2} .0333807{col 40}{space 1}   -5.83{col 49}{space 3}0.000{col 57}{space 4} -.260041{col 70}{space 3}-.1291912
{txt}{space 6}gdpgrowth {c |}{col 17}{res}{space 2} .0027172{col 29}{space 2} .0076719{col 40}{space 1}    0.35{col 49}{space 3}0.723{col 57}{space 4}-.0123194{col 70}{space 3} .0177538
{txt}{space 4}currencynew {c |}{col 17}{res}{space 2}-.2484316{col 29}{space 2} .1147773{col 40}{space 1}   -2.16{col 49}{space 3}0.030{col 57}{space 4}-.4733909{col 70}{space 3}-.0234723
{txt}{space 7}exchrate {c |}{col 17}{res}{space 2} .0000181{col 29}{space 2} .0000188{col 40}{space 1}    0.96{col 49}{space 3}0.335{col 57}{space 4}-.0000187{col 70}{space 3} .0000549
{txt}{space 7}tradelog {c |}{col 17}{res}{space 2}-.0454952{col 29}{space 2} .1078961{col 40}{space 1}   -0.42{col 49}{space 3}0.673{col 57}{space 4}-.2569676{col 70}{space 3} .1659772
{txt}{space 8}polity2 {c |}{col 17}{res}{space 2}-.0180133{col 29}{space 2} .0224869{col 40}{space 1}   -0.80{col 49}{space 3}0.423{col 57}{space 4}-.0620868{col 70}{space 3} .0260603
{txt}{space 8}coldwar {c |}{col 17}{res}{space 2} .2259525{col 29}{space 2} .1242399{col 40}{space 1}    1.82{col 49}{space 3}0.069{col 57}{space 4}-.0175532{col 70}{space 3} .4694582
{txt}{space 5}usalliance {c |}{col 17}{res}{space 2}  .870713{col 29}{space 2} .2579946{col 40}{space 1}    3.37{col 49}{space 3}0.001{col 57}{space 4} .3650528{col 70}{space 3} 1.376373
{txt}{space 8}colbrit {c |}{col 17}{res}{space 2} .0823388{col 29}{space 2} .1835246{col 40}{space 1}    0.45{col 49}{space 3}0.654{col 57}{space 4}-.2773629{col 70}{space 3} .4420404
{txt}{space 9}colfra {c |}{col 17}{res}{space 2} .4634897{col 29}{space 2} .2071608{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4} .0574619{col 70}{space 3} .8695175
{txt}{space 9}eeurop {c |}{col 17}{res}{space 2} .9464524{col 29}{space 2} .2936041{col 40}{space 1}    3.22{col 49}{space 3}0.001{col 57}{space 4} .3709989{col 70}{space 3} 1.521906
{txt}{space 7}lamerica {c |}{col 17}{res}{space 2}-.1898642{col 29}{space 2} .3335188{col 40}{space 1}   -0.57{col 49}{space 3}0.569{col 57}{space 4} -.843549{col 70}{space 3} .4638206
{txt}{space 7}ssafrica {c |}{col 17}{res}{space 2} .6239573{col 29}{space 2} .2208192{col 40}{space 1}    2.83{col 49}{space 3}0.005{col 57}{space 4} .1911596{col 70}{space 3} 1.056755
{txt}{space 11}asia {c |}{col 17}{res}{space 2} .1296539{col 29}{space 2} .2502758{col 40}{space 1}    0.52{col 49}{space 3}0.604{col 57}{space 4}-.3608777{col 70}{space 3} .6201856
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  .978214{col 29}{space 2} 1.013653{col 40}{space 1}    0.97{col 49}{space 3}0.335{col 57}{space 4}-1.008509{col 70}{space 3} 2.964937
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
   /atanhrho_12 {c |}{col 17}{res}{space 2} .4861116{col 29}{space 2} .1585959{col 40}{space 1}    3.07{col 49}{space 3}0.002{col 57}{space 4} .1752694{col 70}{space 3} .7969538
{txt}       /cut_1_1 {c |}{col 17}{res}{space 2}-99.45724{col 29}{space 2} 2.077467{col 40}{space 1}  -47.87{col 49}{space 3}0.000{col 57}{space 4} -103.529{col 70}{space 3}-95.38548
{txt}       /cut_1_2 {c |}{col 17}{res}{space 2} -96.2239{col 29}{space 2} 2.087253{col 40}{space 1}  -46.10{col 49}{space 3}0.000{col 57}{space 4}-100.3148{col 70}{space 3}-92.13296
{txt}       /cut_1_3 {c |}{col 17}{res}{space 2}-93.57091{col 29}{space 2} 2.166325{col 40}{space 1}  -43.19{col 49}{space 3}0.000{col 57}{space 4}-97.81683{col 70}{space 3}-89.32499
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         rho_12{col 17}{c |}{res}{space 2} .4511248{col 29}{space 2} .1263195{col 57}{space 4} .1734965{col 70}{space 3} .6623304
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. corr wecon wopol imfdummy polity2 gdpecon liberalization Dliberalization cedawdummy lntotalfempop civilconflict lagweconglobe lagwopolglobe trend gdpgrowth currency exchrate tradelog coldwar usalliance colbrit colfra nafrme eeurop lamerica ssafrica asia if e(sample)
{txt}(obs=1602)

             {c |}    wecon    wopol imfdummy  polity2  gdpecon libera~n Dliber~n cedawd~y lntota~p civilc~t lagwec~e lagwop~e    trend gdpgro~h curren~w exchrate
{hline 13}{c +}{hline 144}
       wecon {c |}{res}   1.0000
       {txt}wopol {c |}{res}   0.2759   1.0000
    {txt}imfdummy {c |}{res}  -0.0551   0.0258   1.0000
     {txt}polity2 {c |}{res}   0.1984   0.2556   0.0035   1.0000
     {txt}gdpecon {c |}{res}   0.2247  -0.1612  -0.2239   0.0846   1.0000
{txt}liberaliza~n {c |}{res}   0.1997   0.0960  -0.0685   0.3673   0.4408   1.0000
{txt}Dliberaliz~n {c |}{res}  -0.0097   0.0742   0.0699   0.1216   0.0353   0.0832   1.0000
  {txt}cedawdummy {c |}{res}   0.1001   0.3588   0.0870   0.3157   0.0089   0.1853   0.1082   1.0000
{txt}lntotalfem~p {c |}{res}  -0.2199   0.0319  -0.0671  -0.0217  -0.2048  -0.1714   0.0015   0.0742   1.0000
{txt}civilconfl~t {c |}{res}  -0.1829  -0.0677  -0.0253  -0.0181  -0.1630  -0.2077   0.0012   0.0049   0.3060   1.0000
{txt}lagwecongl~e {c |}{res}   0.0136   0.1014   0.0099   0.0500   0.0500   0.1331  -0.0009   0.1165   0.0093  -0.0202   1.0000
{txt}lagwopolgl~e {c |}{res}   0.0319   0.2629   0.0335   0.3053   0.1613   0.4600   0.0918   0.4278   0.0232  -0.0568   0.4822   1.0000
       {txt}trend {c |}{res}   0.0169   0.2662   0.0359   0.3510   0.1627   0.4801   0.1258   0.4742   0.0228  -0.0511   0.2878   0.9436   1.0000
   {txt}gdpgrowth {c |}{res}  -0.0449   0.0245  -0.0060   0.0441   0.0549   0.1873   0.1359   0.0358   0.1071  -0.0314  -0.0075   0.0672   0.0750   1.0000
 {txt}currencynew {c |}{res}  -0.2672  -0.2450   0.0008  -0.9016  -0.2079  -0.4416  -0.1098  -0.2791   0.1603   0.4440  -0.0561  -0.3054  -0.3437  -0.0558   1.0000
    {txt}exchrate {c |}{res}  -0.0686   0.0538   0.0230   0.0435  -0.0383   0.0390  -0.0219   0.0624   0.0569   0.0434   0.0557   0.1475   0.1451  -0.0129  -0.0180   1.0000
    {txt}tradelog {c |}{res}   0.2367   0.0705  -0.0557   0.0816   0.3337   0.4761   0.0111   0.0719  -0.5472  -0.3003   0.0400   0.2165   0.2361   0.0793  -0.2195  -0.0217
     {txt}coldwar {c |}{res}  -0.0395   0.1846   0.0355   0.3382   0.1154   0.3830   0.1745   0.4248   0.0158  -0.0181   0.0422   0.6518   0.8267   0.0693  -0.3155   0.0962
  {txt}usalliance {c |}{res}   0.1223   0.1379   0.0014   0.4574   0.0987   0.1900   0.0120   0.2164   0.0557   0.0132  -0.0172  -0.0123  -0.0091  -0.0694  -0.4074   0.0602
     {txt}colbrit {c |}{res}  -0.0993  -0.1747  -0.0503  -0.0932   0.0785   0.0729  -0.0131  -0.1544  -0.0581  -0.0438   0.0094  -0.0229  -0.0264   0.0602   0.0594  -0.1174
      {txt}colfra {c |}{res}  -0.0202  -0.0120   0.1327  -0.3343  -0.1943  -0.2134  -0.0955  -0.1394  -0.1656  -0.0641  -0.0042  -0.0346  -0.0389  -0.0810   0.2829   0.0020
      {txt}nafrme {c |}{res}  -0.0980  -0.3049  -0.1629  -0.3541   0.1665  -0.0681   0.0109  -0.2357   0.0563   0.0990  -0.0014  -0.0037  -0.0035   0.0354   0.3452  -0.0514
      {txt}eeurop {c |}{res}   0.1625   0.1628   0.0031   0.2208   0.2017   0.0456   0.1864   0.1520  -0.0609  -0.1189   0.0483   0.1813   0.1890   0.0036  -0.2588  -0.0539
    {txt}lamerica {c |}{res}   0.1594   0.1784  -0.0051   0.4075   0.0444   0.1575   0.0123   0.2208  -0.0971  -0.0711  -0.0161  -0.0215  -0.0195  -0.1147  -0.3946   0.0704
    {txt}ssafrica {c |}{res}  -0.1226   0.0188   0.2216  -0.2987  -0.2879  -0.2736  -0.0655  -0.0699  -0.2349  -0.0843  -0.0037  -0.0473  -0.0513  -0.0693   0.2489  -0.0088
        {txt}asia {c |}{res}  -0.0606  -0.0785  -0.1275   0.0501   0.0186   0.1807  -0.0729  -0.0700   0.3896   0.1812  -0.0097  -0.0410  -0.0439   0.1812   0.0299   0.0123

             {txt}{c |} tradelog  coldwar usalli~e  colbrit   colfra   nafrme   eeurop lamerica ssafrica     asia
{hline 13}{c +}{hline 90}
    tradelog {c |}{res}   1.0000
     {txt}coldwar {c |}{res}   0.2072   1.0000
  {txt}usalliance {c |}{res}  -0.1617  -0.0020   1.0000
     {txt}colbrit {c |}{res}   0.1929  -0.0231  -0.3122   1.0000
      {txt}colfra {c |}{res}   0.0115  -0.0351  -0.2709  -0.3796   1.0000
      {txt}nafrme {c |}{res}   0.0009  -0.0011  -0.1719   0.0328   0.1710   1.0000
      {txt}eeurop {c |}{res}   0.2001   0.1464  -0.1535  -0.2034  -0.1621  -0.1116   1.0000
    {txt}lamerica {c |}{res}  -0.1311  -0.0087   0.8551  -0.2923  -0.2154  -0.2269  -0.1765   1.0000
    {txt}ssafrica {c |}{res}  -0.0373  -0.0450  -0.4970   0.1599   0.3910  -0.2735  -0.2128  -0.4325   1.0000
        {txt}asia {c |}{res}   0.0536  -0.0362  -0.1087   0.2490  -0.2645  -0.1822  -0.1417  -0.2881  -0.3473   1.0000

{txt}
{com}. 
. 
. 
. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\dpeksen\Dropbox\Detraz & Peksen paper\Data Files\RandRData and Do Files\DetrazPeksenReplicationLog.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}30 Apr 2015, 15:02:48
{txt}{.-}
{smcl}
{txt}{sf}{ul off}